Tootfinder

See, Think, Act: Teaching Multimodal Agents to Effectively Interact with GUI by Identifying Toggles
Zongru Wu, Rui Mao, Zhiyuan Tian, Pengzhou Cheng, Tianjie Ju, Zheng Wu, Lingzhong Dong, Haiyue Sheng, Zhuosheng Zhang, Gongshen Liu
https://arxiv.org/abs/2509.13615

See, Think, Act: Teaching Multimodal Agents to Effectively Interact with GUI by Identifying Toggles
The advent of multimodal agents facilitates effective interaction within graphical user interface (GUI), especially in ubiquitous GUI control. However, their inability to reliably execute toggle control instructions remains a key bottleneck. To investigate this, we construct a state control benchmark with binary toggle instructions from public datasets. Evaluations of existing agents demonstrate their unreliability, particularly when the current toggle state already matches the desired state. T…

Active Inference Framework for Closed-Loop Sensing, Communication, and Control in UAV Systems
Guangjin Pan, Liping Bai, Zhuojun Tian, Hui Chen, Mehdi Bennis, Henk Wymeersch
https://arxiv.org/abs/2509.14201

Active Inference Framework for Closed-Loop Sensing, Communication, and Control in UAV Systems
Integrated sensing and communication (ISAC) is a core technology for 6G, and its application to closed-loop sensing, communication, and control (SCC) enables various services. Existing SCC solutions often treat sensing and control separately, leading to suboptimal performance and resource usage. In this work, we introduce the active inference framework (AIF) into SCC-enabled unmanned aerial vehicle (UAV) systems for joint state estimation, control, and sensing resource allocation. By formulatin…

Complete Decentralization of Linear Quadratic Gaussian Control for the Discrete Wave Equation
Addie McCurdy, Emily Jensen
https://arxiv.org/abs/2509.13446 https://

Complete Decentralization of Linear Quadratic Gaussian Control for the Discrete Wave Equation
The linear quadratic Gaussian (LQG) control problem for the linear wave equation on the unit circle with fully distributed actuation and partial state measurements is considered. An analytical solution to a spatial discretization of the problem is obtained. The main result of this work illustrates that for specific parameter values, the optimal LQG policy is completely decentralized, meaning only a measurement at spatial location $i$ is needed to compute an optimal control signal to actuate at …

Syndicalist unions are fundamentally different from the bureaucratic trade unions that dominate today. Modern unions function as institutional frameworks that negotiate within capitalism, often acting to preserve the system rather than challenge it. They centralize power in hierarchical leadership, limit direct worker control, and prioritize legal contracts and state approval over genuine worker autonomy.
Syndicalism rejects this institutionalized framework. It refuses collective barga…

The impact of modeling approaches on controlling safety-critical, highly perturbed systems: the case for data-driven models
Piotr {\L}aszkiewicz, Maria Carvalho, Cl\'audia Soares, Pedro Louren\c{c}o
https://arxiv.org/abs/2509.13531

The impact of modeling approaches on controlling safety-critical, highly perturbed systems: the case for data-driven models
This paper evaluates the impact of three system models on the reference trajectory tracking error of the LQR optimal controller, in the challenging problem of guidance and control of the state of a system under strong perturbations and reconfiguration. We compared a smooth Linear Time Variant system learned from data (DD-LTV) with state of the art Linear Time Variant (LTV) system identification methods, showing its superiority in the task of state propagation. Moreover, we have found that DD-LT…

Coherent Driving of a Quantum System with Modulated Free-Space Electrons
Matthias Kolb, Thomas Spielauer, Thomas Weigner, Giovanni Boero, Dennis R\"atzel, Philipp Haslinger
https://arxiv.org/abs/2509.13904

Coherent Driving of a Quantum System with Modulated Free-Space Electrons
Control of quantum systems typically relies on the interaction with electromagnetic radiation. In this study, we experimentally show that the electromagnetic near-field of a spatially modulated freespace electron beam can be used to drive spin systems, demonstrating free-electron-bound-electron resonant interaction. By periodically deflecting the electron beam of a scanning electron microscope in close proximity to a spin-active solid-state sample, and sweeping the deflection frequency across t…

OK... Ceph adventures under control at least for the time being, the cluster is back at HEALTH_OK state.
Back to another round of deprocessing and imaging on the PIC12F683. I have a whole bunch of video I want to shoot but I really want better poly and substrate imagery before I do that, just for eye candy as I'm explaining things.

Gavin Newsom, the California governor,
announced the appointment of two prominent scientists
who left the Centers for Disease Control and Prevention (CDC) in recent months over conflicts with the Trump administration to state positions.
Dr Susan Monarez, the former director of the CDC, will lead California’s new public health initiative, the Public Health Network Innovation Exchange (PHNIX).
In August, Monarez was fired by the Trump administration less than a month in…

Learning Robust Agile Flight Control with Stability Guarantees
Lukas Pries, Markus Ryll
https://arxiv.org/abs/2510.12611 https://arxiv.org/pdf/2510.12611…

Learning Robust Agile Flight Control with Stability Guarantees
In the evolving landscape of high-speed agile quadrotor flight, achieving precise trajectory tracking at the platform's operational limits is paramount. Controllers must handle actuator constraints, exhibit robustness to disturbances, and remain computationally efficient for safety-critical applications. In this work, we present a novel neural-augmented feedback controller for agile flight control. The controller addresses individual limitations of existing state-of-the-art control paradigms an…

This might qualify as a "sophisticated" cyberattack, no?
North Korean state-sponsored hackers hijacked Google accounts to remotely control and wipe smartphones and tablets held by individuals in South Korea, then exploited their KakaoTalk messenger as a channel to spread malware to their contacts

North Korean hackers hijack Google, KakaoTalk accounts to control South Korean phones: Report
The attack marks the first confirmed case of a North Korean state-sponsored hacking group compromising Google accounts. Read more at straitstimes.com. Read more at straitstimes.com.

A framework for realisable data-driven active flow control using model predictive control applied to a simplified truck wake
Alberto Solera-Rico, Carlos Sanmiguel Vila, Stefano Discetti
https://arxiv.org/abs/2510.11600

A framework for realisable data-driven active flow control using model predictive control applied to a simplified truck wake
We present an efficient and realisable active flow control framework with few non-intrusive sensors. The method builds upon data-driven, reduced-order predictive models based on Long-Short-Term Memory (LSTM) networks and efficient gradient-based Model Predictive Control (MPC). The model uses only surface-mounted pressure probes to infer the wake state, and is trained entirely offline on a dataset built with open-loop actuations, thus avoiding the complexities of online learning. Sparsification …

Beyond touch-based HMI: Control your machines in natural language by utilizing large language models and OPC UA
Bernd Hofmann, Sven Kreitlein, Joerg Franke, Patrick Bruendl
https://arxiv.org/abs/2510.11300

Beyond touch-based HMI: Control your machines in natural language by utilizing large language models and OPC UA
This paper proposes an agent-based approach toward a more natural interface between humans and machines. Large language models equipped with tools and the communication standard OPC UA are utilized to control machines in natural language. Instead of touch interaction, which is currently the state-of-the-art medium for interaction in operations, the proposed approach enables operators to talk or text with machines. This allows commands such as 'Please decrease the temperature by 20 % in machine …

Network-Optimised Spiking Neural Network (NOS) Scheduling for 6G O-RAN: Spectral Margin and Delay-Tail Control
Muhammad Bilal, Xiaolong Xu
https://arxiv.org/abs/2510.11291 https…

Network-Optimised Spiking Neural Network (NOS) Scheduling for 6G O-RAN: Spectral Margin and Delay-Tail Control
This work presents a Network-Optimised Spiking (NOS) delay-aware scheduler for 6G radio access. The scheme couples a bounded two-state kernel to a clique-feasible proportional-fair (PF) grant head: the excitability state acts as a finite-buffer proxy, the recovery state suppresses repeated grants, and neighbour pressure is injected along the interference graph via delayed spikes. A small-signal analysis yields a delay-dependent threshold $k_\star(Δ)$ and a spectral margin $δ= k_\star(Δ) - gH…

Control of photoionization by resonant phase-locked pulse pairs
Edvin Olofsson, Evan Lovelle Fulton, Rezvan Tahouri, Mattias Bertolino, Jean Marcel Ngoko Djiokap, Jan Marcus Dahlstr\"om
https://arxiv.org/abs/2510.09441

Control of photoionization by resonant phase-locked pulse pairs
We study the nonlinear and resonant process of two-photon ionization of atoms (He and H) in a pump-probe scheme. The pump pulse prepares the quantum system in a superposition of the ground state and an excited bound state. By varying the phase difference between the pulses, we show how it is possible to coherently control the dressed-state population during the probe pulse. Our main result is that for certain laser parameters, the control over the dressed state population leads to strong contro…

Designing Control Barrier Functions Using a Dynamic Backup Policy
Victor Freire, Marco M. Nicotra
https://arxiv.org/abs/2510.09810 https://arxiv.org/pdf/25…

Designing Control Barrier Functions Using a Dynamic Backup Policy
This paper presents a systematic approach to construct control barrier functions for nonlinear control affine systems subject to arbitrary state and input constraints. Taking inspiration from the reference governor literature, the proposed method defines a family of backup policies, parametrized by the equilibrium manifold of the system. The control barrier function is defined on the augmented state-and-reference space: given a state-reference pair, the approach quantifies the distance to const…

Kontinuous Kontext: Continuous Strength Control for Instruction-based Image Editing
Rishubh Parihar, Or Patashnik, Daniil Ostashev, R. Venkatesh Babu, Daniel Cohen-Or, Kuan-Chieh Wang
https://arxiv.org/abs/2510.08532

Kontinuous Kontext: Continuous Strength Control for Instruction-based Image Editing
Instruction-based image editing offers a powerful and intuitive way to manipulate images through natural language. Yet, relying solely on text instructions limits fine-grained control over the extent of edits. We introduce Kontinuous Kontext, an instruction-driven editing model that provides a new dimension of control over edit strength, enabling users to adjust edits gradually from no change to a fully realized result in a smooth and continuous manner. Kontinuous Kontext extends a state-of-the…

Domino: Dominant Path-based Compensation for Hardware Impairments in Modern WiFi Sensing
Ruiqi Kong, He Chen
https://arxiv.org/abs/2509.13807 https://arxiv…

Domino: Dominant Path-based Compensation for Hardware Impairments in Modern WiFi Sensing
WiFi sensing faces a critical reliability challenge due to hardware-induced RF distortions, especially with modern, market-dominant WiFi cards supporting 802.11ac/ax protocols. These cards employ sensitive automatic gain control and separate RF chains, introducing complex and dynamic distortions that render existing compensation methods ineffective. In this paper, we introduce Domino, a new framework that transforms channel state information (CSI) into channel impulse response (CIR) and leverag…

Tempological Control of Network Dynamics
Yuanzhao Zhang, Sean P. Cornelius
https://arxiv.org/abs/2510.10926 https://arxiv.org/pdf/2510.10926

Tempological Control of Network Dynamics
Feedback control is an effective strategy for stabilizing a desired state and has been widely adopted in maintaining the stability of systems such as flying birds and power grids. By default, this framework requires continuous control input to offset deviations from the desired state, which can be invasive and cost a considerable amount of energy. Here, we introduce tempological (temporal + topological) control -- a novel, noninvasive strategy that harnesses the inherent flexibility of time-var…

A unified optimal control framework: time-optimal control and stochastic optimal control
Shuzhen Yang
https://arxiv.org/abs/2510.07765 https://arxiv.org/pd…

A unified optimal control framework: time-optimal control and stochastic optimal control
In this paper, we propose a unified stochastic optimal control framework that bridges time-optimal control problems and classical stochastic optimal control problems. Unlike traditional deterministic time-optimal control formulations, our framework incorporates a generalized stochastic control structure under minimum-time constraints. Here, the minimum-time condition characterizes the earliest achievable moment for reaching a target state in expectation, rendering the terminal time an endogenou…

❝There was no warning whatsoever. Besides the student programming, there were a number of nationality-based shows, some with 40 years history, displaced and with no chance to transition.❞ https://clevelandstater.com/news/news/csu-shuts-dow…

Co-designing a Programmable RISC-V Accelerator for MPC-based Energy and Thermal Management of Many-Core HPC Processors
Alessandro Ottaviano, Andrino Meli, Paul Scheffler, Giovanni Bambini, Robert Balas, Davide Rossi, Andrea Bartolini, Luca Benini
https://arxiv.org/abs/2510.09163

Co-designing a Programmable RISC-V Accelerator for MPC-based Energy and Thermal Management of Many-Core HPC Processors
Managing energy and thermal profiles is critical for many-core HPC processors with hundreds of application-class processing elements (PEs). Advanced model predictive control (MPC) delivers state-of-the-art performance but requires solving an online optimization problem over a thousand times per second (1 kHz control bandwidth), with computational and memory demands scaling with PE count. Traditional MPC approaches execute the controller on the PEs, but operating system overheads create jitter a…

Bringing Algebraic Hierarchical Decompositions to Concatenative Functional Languages
Attila Egri-Nagy
https://arxiv.org/abs/2510.12481 https://arxiv.org/pd…

Bringing Algebraic Hierarchical Decompositions to Concatenative Functional Languages
Programming languages tend to evolve over time to use more and more concepts from theoretical computer science. Still, there is a gap between programming and pure mathematics. Not all theoretical results have realized their promising applications. The algebraic decomposition of finite state automata (Krohn-Rhodes Theory) constructs an emulating hierarchical structure from simpler components for any computing device. These decompositions provide ways to understand and control computational proce…

The national guard troops Donald Trump sent to Illinois can remain in the state and under federal control
but can’t be deployed, an appeals court ruled on Saturday.
The appeals court granted a pause in the case until it can hear further arguments.
The decision to prevent the troops from protecting federal property or going on patrol comes after federal judge April Perry ruled on Thursday to temporarily block the national guard deployment for at least two weeks,
findin…

https://www.koreaherald.com/article/10612803
NK hackers hijack Google, KakaoTalk accounts to control phones: report

NK hackers hijack Google, KakaoTalk accounts to control phones: report - The Korea Herald
North Korean state-sponsored hackers hijacked Google accounts to remotely control and wipe smartphones and tablets held by individuals in South Korea, then expl

Room temperature optical control of spin states in organic diradicals
Rituparno Chowdhury, Alistair Inglis, Lucy E. Walker, Petri Murto, Chiara Delpiano-Cordeiro, Colin Morrison, Naitik A. Panjwani, Yao Fu, Yan Sun, Wei Zhou, Peter J. Skabara, Akshay Rao, Alexei Chepelianskii, Hugo Bronstein, Sam L. Bayliss, Richard H. Friend
https://arxiv…

Room temperature optical control of spin states in organic diradicals
We report a family of luminescent alternant diradicals which, at room temperature, support a ground-state spin-triplet, near-unity photoluminescence quantum yields, and optical spin addressability. These diradicals comprise trityl groups meta-linked via pyridyl or phenyl groups, enabling optically bright triplet-to-triplet and singlet-to-singlet transitions. At room temperature, we observe optically detected magnetic resonance in these systems at zero magnetic field and a strong magneto-photolu…

A Unidirectionally Connected FAS Approach for 6-DOF Quadrotor Control
Weijie Ren, Haowen Liu, Guang-Ren Duan
https://arxiv.org/abs/2510.12360 https://arxiv…

A Unidirectionally Connected FAS Approach for 6-DOF Quadrotor Control
This paper proposes a unidirectionally connected fully actuated system (UC-FAS) approach for the sub-stabilization and tracking control of 6-DOF quadrotors, tackling limitations both in state-space and FAS framework to some extent. The framework systematically converts underactuated quadrotor dynamics into a UC-FAS model, unifying the existing different FAS transformation ways. By eliminating estimation of the high-order derivatives of control inputs, a drawback of current methods, the UC-FAS m…

"A federal judge [who was appointed by the current potus] in Oregon temporarily blocked President Donald Trump’s administration from deploying the National Guard in Portland, ruling Saturday in a lawsuit brought by the state and city."
https://apnews.…

Federal judge temporarily blocks Trump's plan to deploy National Guard in Portland
A federal judge in Oregon has temporarily blocked President Donald Trump’s administration from deploying the National Guard in Portland. U.S. District Judge Karin Immergut issued the order Saturday in a lawsuit brought by the state and city. The Defense Department had said it was placing 200 members of Oregon’s National Guard under federal control for 60 days to protect federal property at locations where protests are occurring or likely to occur after Trump called the city “war-ravaged.�…

Todd Grantham is out as Oklahoma State defensive coordinator, Clint Bowen will take over https://www.foxsports.com/articles/cfb/todd-grantham-is-out-as-oklahoma-state-defensive-coordinator-clint-bowen-will-take-over

Optimal Control of a Bioeconomic Crop-Energy System with Energy Reinvestment
Othman Cherkaoui Dekkaki
https://arxiv.org/abs/2510.11381 https://arxiv.org/pd…

Optimal Control of a Bioeconomic Crop-Energy System with Energy Reinvestment
We develop an optimal control model for allocating agricultural crop residues between bioenergy production and soil fertility restoration. The system captures a novel circular feedback: a fraction of cumulative energy output is reinvested into soil productivity, linking energy use with ecological regeneration. The dynamics are governed by a nonlinear three-state system describing soil fertility, residue biomass, and accumulated energy, with a single control representing the proportion of biomas…

Voxel-scale quantum state control in nanorod ensembles using reconfigurable needle beams
G. A. Mantashian, D. B. Hayrapetyan, P. A. Mantashyan
https://arxiv.org/abs/2510.07767 h…

Voxel-scale quantum state control in nanorod ensembles using reconfigurable needle beams
Precisely addressing single nanostructures inside dense ensembles remains a bottleneck for scalable photonic and quantum information devices. Here we demonstrate, through comprehensive finite element and variational Monte-Carlo modelling, that a reconfigurable three-dimensional array of needle shaped beams can selectively switch the quantum optical response of individual InAs nanorods embedded in GaAs. By tuning the local non resonant intensity pattern the exciton and biexciton energies were ca…

Replaced article(s) found for cs.RO. https://arxiv.org/list/cs.RO/new
[1/3]:
- Model Predictive Inferential Control of Neural State-Space Models for Autonomous Vehicle Motion P...
Iman Askari, Ali Vaziri, Xuemin Tu, Shen Zeng, Huazhen Fang

A control-based spatial source reconstruction in fractional heat equations
Galina Garc\'ia, Joaqu\'in Vidal, Sebasti\'an Zamorano
https://arxiv.org/abs/2510.07528 ht…

A control-based spatial source reconstruction in fractional heat equations
This article addresses the inverse source problem for a nonlocal heat equation involving the fractional Laplacian. The primary goal is to reconstruct the spatial component of the source term from partial observations of the system's state and its time derivative over a subset of the domain. A reconstruction formula for the Fourier coefficients of the unknown source is derived, leveraging the null controllability property of the fractional heat equation when the fractional order lies in the inte…

Beyond the Use-and-then-Forget (UatF) Bound: Fixed Point Algorithms for Statistical Max-Min Power Control
Renato Luis Garrido Cavalcante, Noor Ul Ain, Lorenzo Miretti, Slawomir Stanczak
https://arxiv.org/abs/2510.11582

Beyond the Use-and-then-Forget (UatF) Bound: Fixed Point Algorithms for Statistical Max-Min Power Control
We introduce mathematical tools and fixed point algorithms for optimal statistical max-min power control in cellular and cell-less massive MIMO systems. Unlike previous studies that rely on the use-and-then-forget (UatF) lower bound on Shannon achievable (ergodic) rates, our proposed framework can deal with alternative bounds that explicitly consider perfect or imperfect channel state information (CSI) at the decoder. In doing so, we address limitations of UatF-based algorithms, which inherit t…

Hallucination-Resistant, Domain-Specific Research Assistant with Self-Evaluation and Vector-Grounded Retrieval
Vivek Bhavsar, Joseph Ereifej, Aravanan Gurusami
https://arxiv.org/abs/2510.02326

Hallucination-Resistant, Domain-Specific Research Assistant with Self-Evaluation and Vector-Grounded Retrieval
Large language models accelerate literature synthesis but can hallucinate and mis-cite, limiting their usefulness in expert workflows. We present RA-FSM (Research Assistant - Finite State Machine), a modular GPT-based research assistant that wraps generation in a finite-state control loop: Relevance -> Confidence -> Knowledge. The system is grounded in vector retrieval and a deterministic citation pipeline. The controller filters out-of-scope queries, scores answerability, decomposes questions,…

I believe the dismantling of capitalism and the state must come through direct action and self-organization by the working class, united in democratic, federated, and recallable unions. Power must grow from the bottom, from the workplaces and communities of ordinary people, instead of being handed to parties or leaders who claim to act on our behalf. Emancipation will only be achieved when workers collectively take control of production, end exploitation, and organize society through free co…

State Constrained Optimal Control Problems With Control On The Acceleration. Applications To Kinetic Mean Field Games
Yves Achdou (LJLL)
https://arxiv.org/abs/2510.07332 https:/…

State Constrained Optimal Control Problems With Control On The Acceleration. Applications To Kinetic Mean Field Games
Relying on the careful study of a related problem in the calculus of variations, we study a class of optimal control problems in which the control lies on the acceleration, with state constraints on the position variable. In dimension one, we find explicit formulas in the special case when the running cost is a power of the acceleration (in absolute value) and the terminal cost is zero. For more general costs or/and higher dimensions, we study the singularities of the value function. We also pr…

Typestate via Revocable Capabilities
Songlin Jia, Craig Liu, Siyuan He, Haotian Deng, Yuyan Bao, Tiark Rompf
https://arxiv.org/abs/2510.08889 https://arxiv…

Typestate via Revocable Capabilities
Managing stateful resources safely and expressively is a longstanding challenge in programming languages, especially in the presence of aliasing. While scope-based constructs such as Java's synchronized blocks offer ease of reasoning, they restrict expressiveness and parallelism. Conversely, imperative, flow-sensitive management enables fine-grained control but demands sophisticated typestate analyses and often burdens programmers with explicit state tracking. In this work, we present a novel…

There tends to be this implicit assumption that only the state can provide services to the people. It's endemic to liberals. If authoritarians seize power, the thinking goes, there's nothing we can do.
But we have ample examples of the opposite. Trumpism is a specific type of authoritarianism where the state withdraws to allow corporations to control most things. They get a degree of autonomy and, in exchange, bow to the sovereign.
This is common in South American dictatorships (often those backed and supported by the US). So it can be helpful to look to these as examples of how to deal with that type of regime.
#USPol

🔦 Molecular switch discovery could open door to male birth control
#molbio

Molecular switch discovery could open door to male birth control
Michigan State University scientists have pinpointed the molecular "switch" that supercharges sperm for their final sprint to an egg—a breakthrough that could reshape infertility treatments and pave the way for safe, nonhormonal male contraceptives. The work is published in the journal Proceedings of the National Academy of Sciences.

Controller for Incremental Input-to-State Practical Stabilization of Partially Unknown systems with Invariance Guarantees
P Sangeerth, David Smith Sundarsingh, Bhabani Shankar Dey, Pushpak Jagtap
https://arxiv.org/abs/2510.10450

Controller for Incremental Input-to-State Practical Stabilization of Partially Unknown systems with Invariance Guarantees
Incremental stability is a property of dynamical systems that ensures the convergence of trajectories with respect to each other rather than a fixed equilibrium point or a fixed trajectory. In this paper, we introduce a related stability notion called incremental input-to-state practical stability (δ-ISpS), ensuring safety guarantees. We also present a feedback linearization based control design scheme that renders a partially unknown system incrementally input-to-state practically stable and …

I wonder how well the low-curiosity people incompetently running our mostly-idle government have understood the nature of who government helps the most.
HINT: If government help was mostly for the poor, we would not have both billionaires and homelessness.
Air traffic control is a state-socialist subsidy service. It exists to make commercial passenger and cargo airlines feasible, an unevenly-distributed benefit. Reducing capacity by 10% won't affect 90% of Americans.
…

Mean Field Type Control Problems Driven by Jump-diffusions
Alain Bensoussan, Ziyu Huang, Shanjian Tang, Sheung Chi Phillip Yam
https://arxiv.org/abs/2509.25614 https://

Mean Field Type Control Problems Driven by Jump-diffusions
In this article, we apply a probabilistic approach to study general mean field type control (MFTC) problems with jump-diffusions, and give the first global-in-time solution. We allow the drift coefficient $b$ and the diffusion coefficient $σ$ to nonlinearly depend on the state, distribution and control variables, and both can be unbounded and possibly degenerate; besides, the jump coefficient $γ$ is allowed to be non-constant. To tackle the non-linear and control-dependent diffusion $σ$, we …

High-Dimensional Statistical Process Control via Manifold Fitting and Learning
Burak I. Tas, Enrique del Castillo
https://arxiv.org/abs/2509.19820 https://…

High-Dimensional Statistical Process Control via Manifold Fitting and Learning
We address the Statistical Process Control (SPC) of high-dimensional, dynamic industrial processes from two complementary perspectives: manifold fitting and manifold learning, both of which assume data lies on an underlying nonlinear, lower dimensional space. We propose two distinct monitoring frameworks for online or 'phase II' Statistical Process Control (SPC). The first method leverages state-of-the-art techniques in manifold fitting to accurately approximate the manifold where the data resi…

Pattern of Extreme Brutality': Tear Gas, Pepper Balls Among Weapons Deployed Against Protesters in Illinois
https://www.bellingcat.com/news/2025/10/31/illinois-immigration-protests/

Tear Gas, Pepper Balls Among Weapons Deployed Against Illinois Protesters
A judge recently issued a restraining order on crowd-control tactics by federal agents in the state, including those involved in Operation Midway Blitz.

Optimal Control of Engineered Swift Equilibration of Nanomechanical Oscillators
Julia Sanders, Paolo Muratore-Ginanneschi
https://arxiv.org/abs/2510.01823 https://

Optimal Control of Engineered Swift Equilibration of Nanomechanical Oscillators
We propose a reformulation of the problem of optimally controlled transitions in stochastic thermodynamics. We impose that any terminal cost specified by a thermodynamic functional should depend only on state variables and not on control protocols, according to the canonical Bolza form. In this way, we can unambiguously discriminate between transitions at minimum dissipation between genuine equilibrium states, and transitions at minimum work driving a system from a genuine equilibrium to a non-…

The Feasibility of Acoustophoresis Multimodal Control
Guilherme Perticarari, Dongjun Wu, Thierry Baasch
https://arxiv.org/abs/2510.06116 https://arxiv.org/…

The Feasibility of Acoustophoresis Multimodal Control
Actuating the acoustic resonance modes of a microfluidic device containing suspended particles (e.g., cells) allows for the manipulation of their individual positions. In this work, we investigate how the number of resonance modes $M$ chosen for actuation and the number of particles $P$ affect the probability of success $S$ of manipulation tasks, denoted Acoustophoretic Control Problems (ACPs). Using simulations, we show that the ratio of locally controllable volume to the state-space volume co…

Three liberal justices won another 10-year term on the Pennsylvania supreme court,
giving Democrats a key victory and allowing them to maintain their 5-2 advantage on a vital body that could issue important rulings on abortion and voting rights in an important battleground state in the coming years.

Multi-State Modeling of Greenhouse Cucumber Yield Dynamics Under Microclimate Effects
Emiliano Seri, Francesco Biso, Gianluigi Bovesecchi, Nikolaos Katsoulas, Cristina Cornaro
https://arxiv.org/abs/2510.11485

Multi-State Modeling of Greenhouse Cucumber Yield Dynamics Under Microclimate Effects
Greenhouse decisions often rely on static thresholds, yet crop output switches among microclimate-driven regimes. We frame daily cucumber yield as transitions among three ordered states and fit a continuous-time, covariate-dependent multistate model. Data come from four greenhouse compartments in Volos, Greece (24 lines, 62 days). States are defined once from control tertiles and applied across compartments. Transition intensities depend on within-compartment z-scores of relative humidity (RH),…

Robust reset control design for piezo-actuated nano-positioner in presence of hysteresis nonlinearity
Ashkan Sebghati, S. Hassan HosseinNia
https://arxiv.org/abs/2510.09445 http…

Robust reset control design for piezo-actuated nano-positioner in presence of hysteresis nonlinearity
In this paper, a robust nonlinear control scheme is designed for the motion control of a class of piezo-actuated nano-positioning systems using frequency-domain analysis. The hysteresis, the nonlinearity in the piezoelectric material, degrades the precision in tracking references with high frequency contents and different travel ranges. The hysteresis compensation by the inverse model, as the state-of-the-art solution, is not reliable alone. Therefore, a control framework with robustness agains…

Ground state magnetic structure of Mn3Sn
Jeppe Jon Cederholm, Zhian Xu, Yanfeng Guo, Martin Ovesen, Thomas Olsen, Kristine M. L. Krighaar, Chrystalla Knekna, Jian Rui Soh, Youngro Lee, Navid Qureshi, Jose Alberto Rodriguez Velamazan, Eric Ressouche, Andrew T. Boothroyd, Henrik Jacobsen
https://arxiv.org/abs/2510.06808

Ground state magnetic structure of Mn3Sn
We use spherical neutron polarimetry to determine the ground state magnetic structure of Mn3Sn. We find that Mn3Sn adopts an inverse triangular structure with spins parallel to <100> (Type III) rather than spins parallel to <110> (Type IV). Density functional theory calculations reveal no energy difference between these two structures, suggesting that the selection is caused by subtle effects such as sixth-order anisotropy. Partial control of the magnetic domain population through a moderate ma…

Packaging of Low-Environmental-Sensitivity WGM Resonators for Practical Applications
Jiajun Wu, Xuanqi Wang, Chengyu Zhang, Chenghong Li, Shan Zhong, Songbai Kang
https://arxiv.org/abs/2510.10939

Packaging of Low-Environmental-Sensitivity WGM Resonators for Practical Applications
We present a prism-coupled packaging strategy for whispering-gallery mode resonators (WGMRs). Utilizing an all-solid-state optical adhesive process with active temperature control and hermetic sealing, the package exhibits exceptional long-term stability and environmental robustness. A standalone WGMR module was characterized, demonstrating a temperature sensitivity below 10^-7 /°C and a low-frequency Z-axis acceleration sensitivity below 10^-10 /g. The module was applied as a stable optical f…

Rivaling Transformers: Multi-Scale Structured State-Space Mixtures for Agentic 6G O-RAN
Farhad Rezazadeh, Hatim Chergui, Merouane Debbah, Houbing Song, Dusit Niyato, Lingjia Liu
https://arxiv.org/abs/2510.05255

Rivaling Transformers: Multi-Scale Structured State-Space Mixtures for Agentic 6G O-RAN
In sixth-generation (6G) Open Radio Access Networks (O-RAN), proactive control is preferable. A key open challenge is delivering control-grade predictions within Near-Real-Time (Near-RT) latency and computational constraints under multi-timescale dynamics. We therefore cast RAN Intelligent Controller (RIC) analytics as an agentic perceive-predict xApp that turns noisy, multivariate RAN telemetry into short-horizon per-User Equipment (UE) key performance indicator (KPI) forecasts to drive antici…

The Age-Structured Chemostat with Substrate Dynamics as a Control System
Iasson Karafyllis, Dionysis Theodosis, Miroslav Krstic
https://arxiv.org/abs/2511.09963 https://arxiv.org/pdf/2511.09963 https://arxiv.org/html/2511.09963
arXiv:2511.09963v1 Announce Type: new
Abstract: In this work we study an age-structured chemostat model with a renewal boundary condition and a coupled substrate equation. The model is nonlinear and consists of a hyperbolic partial differential equation and an ordinary differential equation with nonlinear, nonlocal terms appearing both in the ordinary differential equation and the boundary condition. Both differential equations contain a non-negative control input, while the states of the model are required to be positive. Under an appropriate weak solution framework, we determine the state space and the input space for this model. We prove global existence and uniqueness of solutions for all admissible initial conditions and all allowable control inputs. To this purpose we employ a combination of Banach's fixed-point theorem with implicit solution formulas and useful solution estimates. Finally, we show that the age-structured chemostat model gives a well-defined control system on a metric space.
toXiv_bot_toot

What You Don't Know Can Hurt You: How Well do Latent Safety Filters Understand Partially Observable Safety Constraints?
Matthew Kim, Kensuke Nakamura, Andrea Bajcsy
https://arxiv.org/abs/2510.06492

What You Don't Know Can Hurt You: How Well do Latent Safety Filters Understand Partially Observable Safety Constraints?
Safe control techniques, such as Hamilton-Jacobi reachability, provide principled methods for synthesizing safety-preserving robot policies but typically assume hand-designed state spaces and full observability. Recent work has relaxed these assumptions via latent-space safe control, where state representations and dynamics are learned jointly through world models that reconstruct future high-dimensional observations (e.g., RGB images) from current observations and actions. This enables safety …

Dynamical feedback control with operator learning for the Vlasov-Poisson system
Jingcheng Lu, Li Wang, Jeff Calder
https://arxiv.org/abs/2509.23063 https://

Dynamical feedback control with operator learning for the Vlasov-Poisson system
To meet the demands of instantaneous control of instabilities over long time horizons in plasma fusion, we design a dynamic feedback control strategy for the Vlasov-Poisson system by constructing an operator that maps state perturbations to an external control field. In the first part of the paper, we propose learning such an operator using a neural network. Inspired by optimal control theory for linearized dynamics, we introduce a low-rank neural operator architecture and train it via adjoint …

Stephen Miller is turning the US state department into an
‘anti-immigration machine’
Miller, the president’s immigration czar,
in recent months has turned the state department’s visa and refugee operations into what some current and former diplomats have described as a personal fiefdom.
Each morning, usually at 10am,
a small circle of conservative diplomats allied with Miller,
-- including those who have assumed control of the state department’s consular a…

Anybody have pointers to the current state of the art in SHA-1 collisions?
How much control over the source file is needed? How long does it take? Can you do restricted search space (e.g. no null bytes, nonprintable characters, bytes over 0x20, whatever)?

Anarcho-syndicalism is the belief that workers, as the fundamental producers of social value, must seize control of the means of production through direct action and autonomous organization. It rejects both capitalist private ownership and state-controlled systems, arguing instead for a decentralized federation of worker-managed industries. From my perspective, anarcho-syndicalism is not merely an economic strategy but a revolutionary theory of social transformation, one that places the work…

European "socialism" is a compromise wherein the population gets services and, in exchange, the rich are allowed to continue to exist. This compromise developed to save capitalism from the threat of the working class just rising up and just doing it all themselves. Revolutions, it turns out, can be dangerous and may be subverted. It's generally safer, so Europe's working class decided, to accept some exploitation in exchange for not taking that chance.
The the strategy of "point guns at everyone until they comply" was a sustainable strategy, all of Europe would still be absolute monarchies, feudalism would still be the dominant economic system globally, and England would still control most of the land on Earth. Recognizing that this *isn't* the state of the world should give some clues as to how well Yarvin's ideas continue will play out in the real world.
#USPol

CDE: Concept-Driven Exploration for Reinforcement Learning
Le Mao, Andrew H. Liu, Renos Zabounidis, Zachary Kingston, Joseph Campbell
https://arxiv.org/abs/2510.08851 https://…

CDE: Concept-Driven Exploration for Reinforcement Learning
Intelligent exploration remains a critical challenge in reinforcement learning (RL), especially in visual control tasks. Unlike low-dimensional state-based RL, visual RL must extract task-relevant structure from raw pixels, making exploration inefficient. We propose Concept-Driven Exploration (CDE), which leverages a pre-trained vision-language model (VLM) to generate object-centric visual concepts from textual task descriptions as weak, potentially noisy supervisory signals. Rather than direct…

Inverse Continuous-Time Linear Quadratic Regulator: From Control Cost Matrix to Entire Cost Reconstruction
Yuexin Cao, Yibei Li, Zhuo Zou, Xiaoming Hu
https://arxiv.org/abs/2510.04083

Inverse Continuous-Time Linear Quadratic Regulator: From Control Cost Matrix to Entire Cost Reconstruction
This paper studies the inverse optimal control problem for continuous-time linear quadratic regulators over finite-time horizon, aiming to reconstruct the control, state, and terminal cost matrices in the objective function from observed optimal inputs. Previous studies have mainly explored the recovery of state cost matrices under the assumptions that the system is controllable and the control cost matrix is given. Motivated by various applications in which the control cost matrix is unknown a…

All-optical polarization control in time-varying low-index films via plasma symmetry breaking
Wallace Jaffray, Sven Stengel, Alexandra Boltasseva, Vladimir M. Shalaev, Maria Antonietta Vincenti, Domenico De Ceglia, Michael Scalora, Carlo Rizza, Marcello Ferrera
https://arxiv.org/abs/2510.06985

All-optical polarization control in time-varying low-index films via plasma symmetry breaking
Controlling the polarization state of light with sub-picosecond speed and subwavelength precision remains a key challenge for next-generation nanophotonic devices. Conventional methods such as birefringent crystals, liquid crystals, or electro-optic Pockels cells are limited in speed, compactness, and energy efficiency. While structured materials and two-dimensional heterostructures offer potential for on-chip ultrafast performance, achieving all-optical control remains an open problem. Here we…

A Control Allocation Algorithm for Hypersonic Glide Vehicles with Input Limitations
Johannes Autenrieb, Patrick Gruhn
https://arxiv.org/abs/2510.08275 https://

A Control Allocation Algorithm for Hypersonic Glide Vehicles with Input Limitations
Hypersonic glide vehicles (HGVs) operate in challenging flight regimes characterized by strong nonlinearities in actuation and stringent physical constraints. These include state-dependent actuator limitations, asymmetric control bounds, and thermal loads that vary with maneuvering conditions. This paper introduces an iterative control allocation method to address these challenges in real time. The proposed algorithm searches for control inputs that achieve the desired moment commands while res…

High-Throughput Screening of Transition Metal-Based 2D Multilayer Kagome Materials via the "1 3" Design Strategy
Xing-Yu Wang, En-Qi Bao, Su-Yang Shen, Jun-Hui Yuan, Jiafu Wang
https://arxiv.org/abs/2510.08903

High-Throughput Screening of Transition Metal-Based 2D Multilayer Kagome Materials via the "1 + 3" Design Strategy
Two-dimensional (2D) kagome materials have drawn extensive research interest due to their unique electronic properties, like flat bands, magnetic frustration, and topological quantum states, which enable precise quantum state control and novel device innovation. Yet, simultaneously achieving high stability, tunability, and multifunctionality in 2D kagome systems remains a key material design challenge. In this study, we innovatively propose a new paradigm for constructing two-dimensional multi-…

Riccati-ZORO: An efficient algorithm for heuristic online optimization of internal feedback laws in robust and stochastic model predictive control
Florian Messerer, Yunfan Gao, Jonathan Frey, Moritz Diehl
https://arxiv.org/abs/2511.10473 https://arxiv.org/pdf/2511.10473 https://arxiv.org/html/2511.10473
arXiv:2511.10473v1 Announce Type: new
Abstract: We present Riccati-ZORO, an algorithm for tube-based optimal control problems (OCP). Tube OCPs predict a tube of trajectories in order to capture predictive uncertainty. The tube induces a constraint tightening via additional backoff terms. This backoff can significantly affect the performance, and thus implicitly defines a cost of uncertainty. Optimizing the feedback law used to predict the tube can significantly reduce the backoffs, but its online computation is challenging.
Riccati-ZORO jointly optimizes the nominal trajectory and uncertainty tube based on a heuristic uncertainty cost design. The algorithm alternates between two subproblems: (i) a nominal OCP with fixed backoffs, (ii) an unconstrained tube OCP, which optimizes the feedback gains for a fixed nominal trajectory. For the tube optimization, we propose a cost function informed by the proximity of the nominal trajectory to constraints, prioritizing reduction of the corresponding backoffs. These ideas are developed in detail for ellipsoidal tubes under linear state feedback. In this case, the decomposition into the two subproblems yields a substantial reduction of the computational complexity with respect to the state dimension from $\mathcal{O}(n_x^6)$ to $\mathcal{O}(n_x^3)$, i.e., the complexity of a nominal OCP.
We investigate the algorithm in numerical experiments, and provide two open-source implementations: a prototyping version in CasADi and a high-performance implementation integrated into the acados OCP solver.
toXiv_bot_toot

DH-EAC: Design of a Dynamic, Hierarchical Entanglement Access Control Protocol
Akihisa Takahashi, Yoshito Tobe
https://arxiv.org/abs/2510.02895 https://arx…

DH-EAC: Design of a Dynamic, Hierarchical Entanglement Access Control Protocol
We propose Dynamic, Hierarchical Entanglement Access Control (DH-EAC), a pure-quantum protocol for fair and anonymous allocation of scarce entanglement across wide-area quantum networks composed of many quantum LANs (QLANs). Prior Dicke-state-based pure-quantum MACs resolve contention by local measurements without classical signaling, but they mainly target a single QLAN under static conditions; extending them to wide-area, dynamic settings while avoiding post-selection reconciliation remains o…

Geometry-aware Policy Imitation
Yiming Li, Nael Darwiche, Amirreza Razmjoo, Sichao Liu, Yilun Du, Auke Ijspeert, Sylvain Calinon
https://arxiv.org/abs/2510.08787 https://…

Geometry-aware Policy Imitation
We propose a Geometry-aware Policy Imitation (GPI) approach that rethinks imitation learning by treating demonstrations as geometric curves rather than collections of state-action samples. From these curves, GPI derives distance fields that give rise to two complementary control primitives: a progression flow that advances along expert trajectories and an attraction flow that corrects deviations. Their combination defines a controllable, non-parametric vector field that directly guides robot be…

Dark-fringe interferometer with dynamic phase control for M\"ossbauer science
Miriam Gerharz, Dominik Lentrodt, Lars Bocklage, Kai Schulze, Christian Ott, Ren\'e Steinbr\"ugge, Olaf Leupold, Ilya Sergeev, Gerhard G. Paulus, Christoph H. Keitel, Ralf R\"ohlsberger, Thomas Pfeifer, J\"org Evers
https://arxiv.org/abs/2…

Dark-fringe interferometer with dynamic phase control for Mössbauer science
Interference is a powerful tool for measuring and control. In Mössbauer science, interference effects are essential to most applications, due to the coherent scattering nature. However, Mössbauer interferometry remains challenging, due to stability requirements imposed by the short x-ray wavelength. Here, we put forward a ``dark fringe'' interferometer with vanishing transmission in the empty state, thereby facilitating sensitive measurements. The relative interferometer phase can dynamically…

Stability Preserving Safe Control of a Bicopter
Jhon Manuel Portella Delgado, Ankit Goel
https://arxiv.org/abs/2510.07145 https://arxiv.org/pdf/2510.07145

Stability Preserving Safe Control of a Bicopter
This paper presents a control law for stabilization and trajectory tracking of a multicopter subject to safety constraints. The proposed approach guarantees forward invariance of a prescribed safety set while ensuring smooth tracking performance. Unlike conventional control barrier function methods, the constrained control problem is transformed into an unconstrained one using state-dependent mappings together with carefully constructed Lyapunov functions. This approach enables explicit synthes…

Closed-loop solvability of delayed control problems: A stochastic Volterra system approach
Weijun Meng, Tianxiao Wang, Ji-Feng Zhang
https://arxiv.org/abs/2510.02674 https://

Closed-loop solvability of delayed control problems: A stochastic Volterra system approach
A general and new stochastic linear quadratic optimal control problem is studied, where the coefficients are allowed to be time-varying, and both state delay and control delay can appear simultaneously in the state equation and the cost functional. The closed-loop outcome control of this delayed problem is given by a new Riccati system whose solvability is carefully established. To this end, a novel method is introduced to transform the delayed problem into a control problem driven by a stochas…

California officials are warning foragers after an outbreak of poisoning linked to wild mushrooms that has killed one adult and caused severe liver damage in several patients, including children.
The state poison control system has identified 21 cases of amatoxin poisoning,
likely caused by death cap mushrooms, the health department said Friday.
The toxic wild mushrooms are often mistaken for edible ones because of their appearance and taste.
“Death cap mushrooms con…

Periodic Event-Triggered Prescribed Time Control of Euler-Lagrange Systems under State and Input Constraints
Chidre Shravista Kashyap, Karnan A, Pushpak Jagtap, Jishnu Keshavan
https://arxiv.org/abs/2510.02769

Periodic Event-Triggered Prescribed Time Control of Euler-Lagrange Systems under State and Input Constraints
This article proposes a periodic event-triggered adaptive barrier control policy for the trajectory tracking problem of perturbed Euler-Lagrangian systems with state, input, and temporal (SIT) constraints. In particular, an approximation-free adaptive-barrier control architecture is designed to ensure prescribed-time convergence of the tracking error to a prescribed bound while rejecting exogenous disturbances. In contrast to existing approaches that necessitate continuous real-time control act…

Feature- and process-based optimal control of quantum dynamics
M. Farnia, V. Rezvani, A. T. Rezakhani
https://arxiv.org/abs/2509.22401 https://arxiv.org/pd…

Feature- and process-based optimal control of quantum dynamics
Preparing desired quantum states and quantum operations (processes) is essential for numerous tasks in quantum computation. Several approaches have been developed for optimal control of quantum states, whereas optimal strategies for preparation of a given quantum process have remained fairly less explored. For some applications, rather than a specific desired state or process, it may suffice to obtain states or processes with specific desired features such as (high) coherence or purity. In such…

Adaptive Control Allocation for Underactuated Time-Scale Separated Non-Affine Systems
Daniel M. Cherenson, Dimitra Panagou
https://arxiv.org/abs/2510.07507 https://

Adaptive Control Allocation for Underactuated Time-Scale Separated Non-Affine Systems
Many robotic systems are underactuated, meaning not all degrees of freedom can be directly controlled due to lack of actuators, input constraints, or state-dependent actuation. This property, compounded by modeling uncertainties and disturbances, complicates the control design process for trajectory tracking. In this work, we propose an adaptive control architecture for uncertain, nonlinear, underactuated systems with input constraints. Leveraging time-scale separation, we construct a reduced-o…

Beyond Collision Cones: Dynamic Obstacle Avoidance for Nonholonomic Robots via Dynamic Parabolic Control Barrier Functions
Hun Kuk Park, Taekyung Kim, Dimitra Panagou
https://arxiv.org/abs/2510.01402

Beyond Collision Cones: Dynamic Obstacle Avoidance for Nonholonomic Robots via Dynamic Parabolic Control Barrier Functions
Control Barrier Functions (CBFs) are a powerful tool for ensuring the safety of autonomous systems, yet applying them to nonholonomic robots in cluttered, dynamic environments remains an open challenge. State-of-the-art methods often rely on collision-cone or velocity-obstacle constraints which, by only considering the angle of the relative velocity, are inherently conservative and can render the CBF-based quadratic program infeasible, particularly in dense scenarios. To address this issue, we …

Koopman Control Factorization: Data-Driven Convex Controller Design for a Class of Nonlinear Systems
Taha Ondogan, Ran Jing, Andrew P. Sabelhaus, Roberto Tron
https://arxiv.org/abs/2510.05359

Koopman Control Factorization: Data-Driven Convex Controller Design for a Class of Nonlinear Systems
Although Koopman operators provide a global linearization for autonomous dynamical systems, nonautonomous systems are not globally linear in the inputs. State (or output) feedback controller design therefore remains nonconvex in typical formulations, even with approximations via bilinear control-affine terms. We address this gap by introducing the Koopman Control Factorization, a novel parameterization of control-affine dynamical systems combined with a feedback controller defined as a linear c…

Entangling remote qubits through a two-mode squeezed reservoir
A. Andr\'es-Juanes, J. Agust\'i, R. Sett, E. S. Redchenko, L. Kapoor, S. Hawaldar, P. Rabl, J. M. Fink
https://arxiv.org/abs/2510.07139

Entangling remote qubits through a two-mode squeezed reservoir
The distribution of entanglement across distant qubits is a central challenge for the operation of scalable quantum computers and large-scale quantum networks. Existing approaches rely on deterministic state transfer schemes or probabilistic protocols that require active control or measurement and postselection. Here we demonstrate an alternative, fully autonomous process, where two remote qubits are entangled through their coupling to a quantum-correlated photonic reservoir. In our experiment,…

Replaced article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- A robust BFGS algorithm for unconstrained nonlinear optimization problems
Yaguang Yang
https://arxiv.org/abs/1212.5929
- Quantum computing and the stable set problem
Alja\v{z} Krpan, Janez Povh, Dunja Pucher
https://arxiv.org/abs/2405.12845 https://mastoxiv.page/@arXiv_mathOC_bot/112483516437815686
- Mean Field Game with Reflected Jump Diffusion Dynamics: A Linear Programming Approach
Zongxia Liang, Xiang Yu, Keyu Zhang
https://arxiv.org/abs/2508.20388 https://mastoxiv.page/@arXiv_mathOC_bot/115111048711698998
- Differential Dynamic Programming for the Optimal Control Problem with an Ellipsoidal Target Set a...
Sungjun Eom, Gyunghoon Park
https://arxiv.org/abs/2509.07546 https://mastoxiv.page/@arXiv_mathOC_bot/115179281556444440
- On the Moreau envelope properties of weakly convex functions
Marien Renaud, Arthur Leclaire, Nicolas Papadakis
https://arxiv.org/abs/2509.13960 https://mastoxiv.page/@arXiv_mathOC_bot/115224514482363803
- Automated algorithm design via Nevanlinna-Pick interpolation
Ibrahim K. Ozaslan, Tryphon T. Georgiou, Mihailo R. Jovanovic
https://arxiv.org/abs/2509.21416 https://mastoxiv.page/@arXiv_mathOC_bot/115286533597711930
- Optimal Control of a Bioeconomic Crop-Energy System with Energy Reinvestment
Othman Cherkaoui Dekkaki
https://arxiv.org/abs/2510.11381 https://mastoxiv.page/@arXiv_mathOC_bot/115372322896073250
- Point Convergence Analysis of the Accelerated Gradient Method for Multiobjective Optimization: Co...
Yingdong Yin
https://arxiv.org/abs/2510.26382 https://mastoxiv.page/@arXiv_mathOC_bot/115468018035252078
- History-Aware Adaptive High-Order Tensor Regularization
Chang He, Bo Jiang, Yuntian Jiang, Chuwen Zhang, Shuzhong Zhang
https://arxiv.org/abs/2511.05788
- Equivalence of entropy solutions and gradient flows for pressureless 1D Euler systems
Jos\'e Antonio Carrillo, Sondre Tesdal Galtung
https://arxiv.org/abs/2312.04932 https://mastoxiv.page/@arXiv_mathAP_bot/111560077272113052
- Kernel Modelling of Fading Memory Systems
Yongkang Huo, Thomas Chaffey, Rodolphe Sepulchre
https://arxiv.org/abs/2403.11945 https://mastoxiv.page/@arXiv_eessSY_bot/112121123836064435
- The Maximum Theoretical Ground Speed of the Wheeled Vehicle
Altay Zhakatayev, Mukatai Nemerebayev
https://arxiv.org/abs/2502.15341 https://mastoxiv.page/@arXiv_physicsclassph_bot/114057765769441123
- Hessian stability and convergence rates for entropic and Sinkhorn potentials via semiconcavity
Giacomo Greco, Luca Tamanini
https://arxiv.org/abs/2504.11133 https://mastoxiv.page/@arXiv_mathPR_bot/114346453424694503
- Optimizing the ground state energy of the three-dimensional magnetic Dirichlet Laplacian with con...
Matthias Baur
https://arxiv.org/abs/2504.21597 https://mastoxiv.page/@arXiv_mathph_bot/114431404740241516
- A localized consensus-based sampling algorithm
Arne Bouillon, Alexander Bodard, Panagiotis Patrinos, Dirk Nuyens, Giovanni Samaey
https://arxiv.org/abs/2505.24861 https://mastoxiv.page/@arXiv_mathNA_bot/114612580684567066
- A Novel Sliced Fused Gromov-Wasserstein Distance
Moritz Piening, Robert Beinert
https://arxiv.org/abs/2508.02364 https://mastoxiv.page/@arXiv_csLG_bot/114976243138728278
- Minimal Regret Walras Equilibria for Combinatorial Markets via Duality, Integrality, and Sensitiv...
Alo\"is Duguet, Tobias Harks, Martin Schmidt, Julian Schwarz
https://arxiv.org/abs/2511.09021 https://mastoxiv.page/@arXiv_csGT_bot/115541243299714775
toXiv_bot_toot

Delay Independent Safe Control with Neural Networks: Positive Lur'e Certificates for Risk Aware Autonomy
Hamidreza Montazeri Hedesh, Milad Siami
https://arxiv.org/abs/2510.06661

Delay Independent Safe Control with Neural Networks: Positive Lur'e Certificates for Risk Aware Autonomy
We present a risk-aware safety certification method for autonomous, learning enabled control systems. Focusing on two realistic risks, state/input delays and interval matrix uncertainty, we model the neural network (NN) controller with local sector bounds and exploit positivity structure to derive linear, delay-independent certificates that guarantee local exponential stability across admissible uncertainties. To benchmark performance, we adopt and implement a state-of-the-art IQC NN verificati…

Learning-based model predictive control with moving horizon state estimation for autonomous racing
Yassine Kebbati, Andreas Rauh, Naima Ait-Oufroukh, Dalil Ichalal, Vincent Vigneron
https://arxiv.org/abs/2510.05366

Learning-based model predictive control with moving horizon state estimation for autonomous racing
This paper addresses autonomous racing by introducing a real-time nonlinear model predictive controller (NMPC) coupled with a moving horizon estimator (MHE). The racing problem is solved by an NMPC-based off-line trajectory planner that computes the best trajectory while considering the physical limits of the vehicle and circuit constraints. The developed controller is further enhanced with a learning extension based on Gaussian process regression that improves model predictions. The proposed c…

It is notable that the state and local police are all friendly witnesses for the plaintiffs in these cases
https://bsky.app/profile/kyledcheney.bsky.social/post/3m4dzxfbwak2q

Kyle Cheney (@kyledcheney.bsky.social)
HAPPENING NOW: Portland Police Commander Franz Schoening testifies that federal officers on Oct. 18 barraged protesters with crowd control munitions — not because of any violence but because another federal officer accidentally shot tear gas onto the roof of the ICE facility.

PoseDiff: A Unified Diffusion Model Bridging Robot Pose Estimation and Video-to-Action Control
Haozhuo Zhang, Michele Caprio, Jing Shao, Qiang Zhang, Jian Tang, Shanghang Zhang, Wei Pan
https://arxiv.org/abs/2509.24591

PoseDiff: A Unified Diffusion Model Bridging Robot Pose Estimation and Video-to-Action Control
We present PoseDiff, a conditional diffusion model that unifies robot state estimation and control within a single framework. At its core, PoseDiff maps raw visual observations into structured robot states-such as 3D keypoints or joint angles-from a single RGB image, eliminating the need for multi-stage pipelines or auxiliary modalities. Building upon this foundation, PoseDiff extends naturally to video-to-action inverse dynamics: by conditioning on sparse video keyframes generated by world mod…

Control of Conservation Laws in the Nonlocal-to-Local Limit
Jan Friedrich, Michael Herty, Claudia Nocita
https://arxiv.org/abs/2510.00677 https://arxiv.org…

Control of Conservation Laws in the Nonlocal-to-Local Limit
We analyze a class of control problems where the initial datum acts as a control and the state is given by the entropy solution of (local) conservation laws by a nonlocal-to-local limiting strategy. In particular we characterize the limit up to subsequence of minimizers to nonlocal control problems as minimizer of the corresponding local ones. Moreover, we also prove an analogous result at a discrete level by means of a Eulerian-Lagrangian scheme.

Pixel Motion Diffusion is What We Need for Robot Control
E-Ro Nguyen, Yichi Zhang, Kanchana Ranasinghe, Xiang Li, Michael S. Ryoo
https://arxiv.org/abs/2509.22652 https://

Pixel Motion Diffusion is What We Need for Robot Control
We present DAWN (Diffusion is All We Need for robot control), a unified diffusion-based framework for language-conditioned robotic manipulation that bridges high-level motion intent and low-level robot action via structured pixel motion representation. In DAWN, both the high-level and low-level controllers are modeled as diffusion processes, yielding a fully trainable, end-to-end system with interpretable intermediate motion abstractions. DAWN achieves state-of-the-art results on the challengin…

The Trump administration is dismantling the last of the public commons.
It’s cutting billions to state programs tracking disease,
repealing emissions and drinking water regulations,
revoking hundreds of millions in funding for life-saving research,
canceling local food programs for schools and food banks,
rolling back vaccinations,
and shutting down the Centers for Disease Control and Prevention’s (CDC’s) Healthcare Infection Control Practices Advisory Commi…

“Make America Healthy Again” Aims to Make Public Health Your Private Responsibility
The message coming from the Trump administration is: “Take care of yourselves — because we won’t.”…

A Variational Calculus for Optimal Control of the Generalized Riemann Problem for Hyperbolic Systems of Conservation Laws
Jannik Breitkopf, Stefan Ulbrich
https://arxiv.org/abs/2509.22076

A Variational Calculus for Optimal Control of the Generalized Riemann Problem for Hyperbolic Systems of Conservation Laws
We develop a variational calculus for entropy solutions of the Generalized Riemann Problem (GRP) for strictly hyperbolic systems of conservation laws where the control is the initial state. The GRP has a discontinuous initial state with exactly one discontinuity and continuously differentiable ($C^1$) states left and right of it. The control consists of the $C^1$ parts of the initial state and the position of the discontinuity. Solutions of the problem are generally discontinuous since they con…

Memory-Augmented Potential Field Theory: A Framework for Adaptive Control in Non-Convex Domains
Dongzhe Zheng, Wenjie Mei
https://arxiv.org/abs/2509.19672 https://

Memory-Augmented Potential Field Theory: A Framework for Adaptive Control in Non-Convex Domains
Stochastic optimal control methods often struggle in complex non-convex landscapes, frequently becoming trapped in local optima due to their inability to learn from historical trajectory data. This paper introduces Memory-Augmented Potential Field Theory, a unified mathematical framework that integrates historical experience into stochastic optimal control. Our approach dynamically constructs memory-based potential fields that identify and encode key topological features of the state space, ena…

CPU- and GPU-Based Parallelization of the Robust Reference Governor
Hamid R. Ossareh, William Shayne, Samuel Chevalier
https://arxiv.org/abs/2510.08288 https://

CPU- and GPU-Based Parallelization of the Robust Reference Governor
Constraint management is a central challenge in modern control systems. A solution is the Reference Governor (RG), which is an add-on strategy to pre-stabilized feedback control systems to enforce state and input constraints by shaping the reference command. While robust formulations of RG exist for linear systems, their extension to nonlinear systems is often computationally intractable. This paper develops a scenario-based robust RG formulation for nonlinear systems and investigates its paral…

Funnel control for passive infinite-dimensional systems
Thavamani Govindaraj, Anthony Hastir, Lassi Paunonen, Timo Reis
https://arxiv.org/abs/2510.01027 https://

Funnel control for passive infinite-dimensional systems
We consider funnel control for linear infinite-dimensional systems that are impedance passive, meaning that they satisfy an energy balance in which the stored energy equals the squared norm of the state and the supplied power is the inner product of input and output. For the analysis we employ the system node approach, which offers a unified framework for infinite-dimensional systems with boundary and distributed control and observation. The resulting closed-loop dynamics are governed by a nonl…

Guaranteed Time Control using Linear Matrix Inequalities
V\'ictor Costa da Silva Campos, Mariella Maia Quadros, Luciano Frezzato, Leonardo Mozelli, Anh-Tu Nguyen
https://arxiv.org/abs/2510.02636

Guaranteed Time Control using Linear Matrix Inequalities
This paper presents a synthesis approach aiming to guarantee a minimum upper-bound for the time taken to reach a target set of non-zero measure that encompasses the origin, while taking into account uncertainties and input and state constraints. This approach is based on a harmonic transformation of the Lyapunov function and a novel piecewise quadratic representation of this transformed Lyapunov function over a simplicial partition of the state space. The problem is solved in a policy iteration…

Rich State Observations Empower Reinforcement Learning to Surpass PID: A Drone Ball Balancing Study
Mingjiang Liu, Hailong Huang
https://arxiv.org/abs/2509.21122 https://…

Rich State Observations Empower Reinforcement Learning to Surpass PID: A Drone Ball Balancing Study
This paper addresses a drone ball-balancing task, in which a drone stabilizes a ball atop a movable beam through cable-based interaction. We propose a hierarchical control framework that decouples high-level balancing policy from low-level drone control, and train a reinforcement learning (RL) policy to handle the high-level decision-making. Simulation results show that the RL policy achieves superior performance compared to carefully tuned PID controllers within the same hierarchical structure…

Safe Stabilization of the Stefan Problem with a High-Order Moving Boundary Dynamics by PDE Backstepping
Shumon Koga, Miroslav Krstic
https://arxiv.org/abs/2510.06571 https://

Safe Stabilization of the Stefan Problem with a High-Order Moving Boundary Dynamics by PDE Backstepping
This paper presents a safe stabilization of the Stefan PDE model with a moving boundary governed by a high-order dynamics. We consider a parabolic PDE with a time-varying domain governed by a second-order response with respect to the Neumann boundary value of the PDE state at the moving boundary. The objective is to design a boundary heat flux control to stabilize the moving boundary at a desired setpoint, with satisfying the required conditions of the model on PDE state and the moving boundary…

A Bilevel Optimization Framework for Adversarial Control of Gas Pipeline Operations
Tejaswini Sanjay Katale, Lu Gao, Yunpeng Zhang, Alaa Senouci
https://arxiv.org/abs/2510.02503

A Bilevel Optimization Framework for Adversarial Control of Gas Pipeline Operations
Cyberattacks on pipeline operational technology systems pose growing risks to energy infrastructure. This study develops a physics-informed simulation and optimization framework for analyzing cyber-physical threats in petroleum pipeline networks. The model integrates networked hydraulic dynamics, SCADA-based state estimation, model predictive control (MPC), and a bi-level formulation for stealthy false-data injection (FDI) attacks. Pipeline flow and pressure dynamics are modeled on a directed g…

On the Boundary of the Robust Admissible Set in State and Input Constrained Nonlinear Systems
Franz Ru{\ss}wurm, Jean L\'evine, Stefan Streif
https://arxiv.org/abs/2509.18825

On the Boundary of the Robust Admissible Set in State and Input Constrained Nonlinear Systems
In this paper, we consider nonlinear control systems subject to bounded disturbances and to both state and input constraints. We introduce the definition of robust admissible set - the set of all initial states from which the state and input constraints can be satisfied for all times against all admissible disturbances. We focus on its boundary that can be decomposed into the usable part on the state constraint boundary and the barrier, interior to the state constraints. We show that, at the in…

Quasi-Ergodic Control of Multi-Periodic Autoregressive Processes: Formulation and Examples
Vyacheslav Kungurtsev
https://arxiv.org/abs/2509.24729 https://a…

Quasi-Ergodic Control of Multi-Periodic Autoregressive Processes: Formulation and Examples
This work considers state dynamics driven by Periodic Autoregressive Moving Average noise, and control of the system over time. Such processes appear frequently in applications involving the environment, such as energy and agriculture. Managing these systems applying forecasts to make decisions that exhibit foresight and risk aversion while maximizing profits is a challenging control problem that can be computationally difficult for standard scenario- based methods. This paper presents a formul…

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators
Gianluca Fabiani, Constantinos Siettos, Ioannis G. Kevrekidis
https://arxiv.org/abs/2509.23975

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators
The control of high-dimensional distributed parameter systems (DPS) remains a challenge when explicit coarse-grained equations are unavailable. Classical equation-free (EF) approaches rely on fine-scale simulators treated as black-box timesteppers. However, repeated simulations for steady-state computation, linearization, and control design are often computationally prohibitive, or the microscopic timestepper may not even be available, leaving us with data as the only resource. We propose a dat…

Optimal Control in Infinite Dimensional Spaces and Economic Modeling: State of the Art and Perspectives
Giorgio Fabbri, Silvia Faggian, Salvatore Federico, Fausto Gozzi
https://arxiv.org/abs/2509.19909

Optimal Control in Infinite Dimensional Spaces and Economic Modeling: State of the Art and Perspectives
This survey collects, within a unified framework, various results (primarily by the authors themselves) on the use of Deterministic Infinite-Dimensional Optimal Control Theory to address applied economic models. The main aim is to illustrate, through several examples, the typical features of such models (including state constraints, non-Lipschitz data, and non-regularizing differential operators) and the corresponding methods needed to handle them. This necessitates developing aspects of the ex…

Predictive Control Barrier Functions for Discrete-Time Linear Systems with Unmodeled Delays
Juan Augusto Paredes Salazar, James Usevitch, Ankit Goel
https://arxiv.org/abs/2510.01059

Predictive Control Barrier Functions for Discrete-Time Linear Systems with Unmodeled Delays
This paper introduces a predictive control barrier function (PCBF) framework for enforcing state constraints in discrete-time systems with unknown relative degree, which can be caused by input delays or unmodeled input dynamics. Existing discrete-time CBF formulations typically require the construction of auxiliary barrier functions when the relative degree is greater than one, which complicates implementation and may yield conservative safe sets. The proposed PCBF framework addresses this chal…

Control and Navigation of a 2-D Electric Rocket
Andr\'e Fonte, Pedro Santos, Paulo Oliveira
https://arxiv.org/abs/2509.19970 https://arxiv.org/pdf/2509…

Control and Navigation of a 2-D Electric Rocket
This work addresses the control and navigation of a simulated two-dimensional electric rocket. The model provides a simplified framework that neglects actuator dynamics and aerodynamic effects while capturing the complexities of underactuation and state coupling. Trajectory tracking is achieved through a modularized and layered control architecture, with employement of a Linear Quadratic Regulator (LQR) and Lyapunov theory. Full-state estimation is achieved through Kalman filtering techniques, …

MM-LMPC: Multi-Modal Learning Model Predictive Control via Bandit-Based Mode Selection
Wataru Hashimoto, Kazumune Hashimoto
https://arxiv.org/abs/2510.00410 https://

MM-LMPC: Multi-Modal Learning Model Predictive Control via Bandit-Based Mode Selection
Learning Model Predictive Control (LMPC) improves performance on iterative tasks by leveraging data from previous executions. At each iteration, LMPC constructs a sampled safe set from past trajectories and uses it as a terminal constraint, with a terminal cost given by the corresponding cost-to-go. While effective, LMPC heavily depends on the initial trajectories: states with high cost-to-go are rarely selected as terminal candidates in later iterations, leaving parts of the state space unexpl…