Tootfinder

Viscosity CBFs: Bridging the Control Barrier Function and Hamilton-Jacobi Reachability Frameworks in Safe Control Theory
Dylan Hirsch, Jaime Fern\'andez Fisac, Sylvia Herbert
https://arxiv.org/abs/2510.09929

Viscosity CBFs: Bridging the Control Barrier Function and Hamilton-Jacobi Reachability Frameworks in Safe Control Theory
Control barrier functions (CBFs) and Hamilton-Jacobi reachability (HJR) are central frameworks in safe control. Traditionally, these frameworks have been viewed as distinct, with the former focusing on optimally safe controller design and the latter providing sufficient conditions for safety. A previous work introduced the notion of a control barrier value function (CB-VF), which is defined similarly to the other value functions studied in HJR but has certain CBF-like properties. In this work, …

Crosslisted article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- Optimal control of Volterra integral diffusions and application to contract theory
Dylan Possama\"i, Mehdi Talbi
https://arxiv.org/abs/2511.09701 https://mastoxiv.page/@arXiv_mathPR_bot/115547093766733637
- Generalized infinite dimensional Alpha-Procrustes based geometries
Salvish Goomanee, Andi Han, Pratik Jawanpuria, Bamdev Mishra
https://arxiv.org/abs/2511.09801 https://mastoxiv.page/@arXiv_statML_bot/115547135711272091
- Sample Complexity of Quadratically Regularized Optimal Transport
Alberto Gonz\'alez-Sanz, Eustasio del Barrio, Marcel Nutz
https://arxiv.org/abs/2511.09807 https://mastoxiv.page/@arXiv_mathST_bot/115546975796760368
- On the Convergence of Overparameterized Problems: Inherent Properties of the Compositional Struct...
Arthur Castello Branco de Oliveira, Dhruv Jatkar, Eduardo Sontag
https://arxiv.org/abs/2511.09810 https://mastoxiv.page/@arXiv_csLG_bot/115547543989283588
- Implicit Multiple Tensor Decomposition
Kunjing Yang, Libin Zheng, Minru Bai
https://arxiv.org/abs/2511.09916 https://mastoxiv.page/@arXiv_mathNA_bot/115547169767663335
- Theoretical Analysis of Resource-Induced Phase Transitions in Estimation Strategies
Takehiro Tottori, Tetsuya J. Kobayashi
https://arxiv.org/abs/2511.10184 https://mastoxiv.page/@arXiv_physicsbioph_bot/115546979073652600
- Zeroes and Extrema of Functions via Random Measures
Athanasios Christou Micheas
https://arxiv.org/abs/2511.10293 https://mastoxiv.page/@arXiv_statME_bot/115547493525198835
- Operator Models for Continuous-Time Offline Reinforcement Learning
Nicolas Hoischen, Petar Bevanda, Max Beier, Stefan Sosnowski, Boris Houska, Sandra Hirche
https://arxiv.org/abs/2511.10383 https://mastoxiv.page/@arXiv_statML_bot/115547254989932993
- On topological properties of closed attractors
Wouter Jongeneel
https://arxiv.org/abs/2511.10429 https://mastoxiv.page/@arXiv_mathDS_bot/115547276594491411
- Learning parameter-dependent shear viscosity from data, with application to sea and land ice
Gonzalo G. de Diego, Georg Stadler
https://arxiv.org/abs/2511.10452 https://mastoxiv.page/@arXiv_mathNA_bot/115547323782478749
- Formal Verification of Control Lyapunov-Barrier Functions for Safe Stabilization with Bounded Con...
Jun Liu
https://arxiv.org/abs/2511.10510 https://mastoxiv.page/@arXiv_eessSY_bot/115547429321496393
- Direction-of-Arrival and Noise Covariance Matrix joint estimation for beamforming
Vitor Gelsleichter Probst Curtarelli
https://arxiv.org/abs/2511.10639 https://mastoxiv.page/@arXiv_eessAS_bot/115547188796143762
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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…

Control variates from Eulerian and Lagrangian perturbation theory: Application to the bispectrum
Nickolas Kokron, Shi-Fan Chen
https://arxiv.org/abs/2510.07375 https://

Control variates from Eulerian and Lagrangian perturbation theory: Application to the bispectrum
Control variates have seen recent interest as a powerful technique to reduce the variance of summary statistics measured from costly cosmological $N$-body simulations. Of particular interest are the class of control variates which are analytically calculable, such as the recently introduced 'Zeldovich control variates' for the power spectrum of matter and biased tracers. In this work we present the construction of perturbative control variates in Eulerian and Lagrangian perturbation theory, and…

Fast and the Furious: Hot Starts in Pursuit-Evasion Games
Gabriel Smithline, Scott Nivison
https://arxiv.org/abs/2510.10830 https://arxiv.org/pdf/2510.1083…

Fast and the Furious: Hot Starts in Pursuit-Evasion Games
Effectively positioning pursuers in pursuit-evasion games without prior knowledge of evader locations remains a significant challenge. A novel approach that combines game-theoretic control theory with Graph Neural Networks is introduced in this work. By conceptualizing pursuer configurations as strategic arrangements and representing them as graphs, a Graph Characteristic Space is constructed via multi-objective optimization to identify Pareto-optimal configurations. A Graph Convolutional Netwo…

Certifying Quantum Gates via Automata Advantage
Anna Schroeder, Lucas B. Vieira, Jan N\"oller, Nikolai Miklin, Mariami Gachechiladze
https://arxiv.org/abs/2510.09575 https:…

Certifying Quantum Gates via Automata Advantage
There is growing interest in developing rigorous tests of quantumness that are feasible even before practical quantum advantages become a reality. Such tests not only aim to certify the quantum nature of a system but also serve as benchmarks for precise quantum control. In this work, we argue that promise problems, studied in the theory of finite automata, provide a natural framework for designing sound tests of quantum gate quality. Soundness, the property that only implementations of sufficie…

Architecture Induces Structural Invariant Manifolds of Neural Network Training Dynamics
Jiajie Zhao, Tao Luo, Yaoyu Zhang
https://arxiv.org/abs/2510.09564 https://

Architecture Induces Structural Invariant Manifolds of Neural Network Training Dynamics
While architecture is recognized as key to the performance of deep neural networks, its precise effect on training dynamics has been unclear due to the confounding influence of data and loss functions. This paper proposed an analytic framework based on the geometric control theory to characterize the dynamical properties intrinsic to a model's parameterization. We prove that the Structural Invariant Manifolds (SIMs) of an analytic model $F(\mathbfθ)(\mathbf{x})$--submanifolds that confine grad…

One rig to control them all
Chris Heunen, Robin Kaarsgaard, Louis Lemonnier
https://arxiv.org/abs/2510.05032 https://arxiv.org/pdf/2510.05032

One rig to control them all
We introduce a theory for computational control, consisting of seven naturally interpretable equations. Adding these to a prop of base circuits constructs controlled circuits, borne out in examples of reversible Boolean circuits and quantum circuits. We prove that this syntactic construction semantically corresponds to taking the free rig category on the base prop.

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…

Optimization via a Control-Centric Framework
Liraz Mudrik, Isaac Kaminer, Sean Kragelund, Abram H. Clark
https://arxiv.org/abs/2510.05455 https://arxiv.org…

Optimization via a Control-Centric Framework
Optimization plays a central role in intelligent systems and cyber-physical technologies, where the speed and reliability of convergence directly impact performance. In control theory, optimization-centric methods are standard: controllers are designed by repeatedly solving optimization problems, as in linear quadratic regulation, $H_\infty$ control, and model predictive control. In contrast, this paper develops a control-centric framework for optimization itself, where algorithms are construct…

An efficient grey theory-driven path selection for energy efficiency control in the Internet of Things using fog and cloud computing
Mohammad Reza Akbari, Hamid Barati, Ali Barati
https://arxiv.org/abs/2510.03533

An efficient grey theory-driven path selection for energy efficiency control in the Internet of Things using fog and cloud computing
Due to the big data exchange on the Internet of Things, proper routing and selecting the best routes for fast data transmission improve network performance. There are major challenges, like high delay, when cloud computing is used. Therefore, one solution is to use other schemes, such as fog computing. In fog computing, all data is not sent to the cloud and the fog nodes close to objects are used for data processing. This reduces the network delay. In this paper, we propose an overlapping clust…

Magnetic-Field Control of Tomonaga-Luttinger Liquids in Ta2Pd3Te5 Edge States
Xingchen Guo Anqi Wang, Xiutong Deng, Yupeng Li, Guoan Li, Zhiyuan Zhang, Xiaofan Shi, Xiao Deng, Ziwei Dou, Guangtong Liu, Fanming Qu, Zhijun Wang, Tian Qian, Youguo Shi, Li Lu, Jie Shen
https://arxiv.org/abs/2510.07973 …

Magnetic-Field Control of Tomonaga-Luttinger Liquids in Ta2Pd3Te5 Edge States
Ta2Pd3Te5 is a quasi-one-dimensional transition-metal telluride whose heavy atoms endow the material with strong spin-orbit coupling, while the Fermi level inside the bulk gap makes the low-energy electronic structure highly tunable.Theory and early experiments have already identified a wealth of emergent phases in this platform: an excitonic insulator driven by electron-hole binding, a second-order topological insulator protected by crystalline symmetry, a potential topological-protected quant…

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…

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 …

Crosslisted article(s) found for math.CT. https://arxiv.org/list/math.CT/new
[1/1]:
- One rig to control them all
Chris Heunen, Robin Kaarsgaard, Louis Lemonnier

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…

Attention Schema-based Attention Control (ASAC): A Cognitive-Inspired Approach for Attention Management in Transformers
Krati Saxena, Federico Jurado Ruiz, Guido Manzi, Dianbo Liu, Alex Lamb
https://arxiv.org/abs/2509.16058

Attention Schema-based Attention Control (ASAC): A Cognitive-Inspired Approach for Attention Management in Transformers
Attention mechanisms have become integral in AI, significantly enhancing model performance and scalability by drawing inspiration from human cognition. Concurrently, the Attention Schema Theory (AST) in cognitive science posits that individuals manage their attention by creating a model of the attention itself, effectively allocating cognitive resources. Inspired by AST, we introduce ASAC (Attention Schema-based Attention Control), which integrates the attention schema concept into artificial n…

Replaced article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Optimal Modified Feedback Strategies in LQ Games under Control Imperfections
Mahdis Rabbani, Navid Mojahed, Shima Nazari

Machine Learning and Control: Foundations, Advances, and Perspectives
Enrique Zuazua
https://arxiv.org/abs/2510.03303 https://arxiv.org/pdf/2510.03303

Machine Learning and Control: Foundations, Advances, and Perspectives
Control theory of dynamical systems offers a powerful framework for tackling challenges in deep neural networks and other machine learning architectures. We show that concepts such as simultaneous and ensemble controllability offer new insights into the classification and representation properties of deep neural networks while the control and optimization of static systems can be employed to better understand the performance of shallow networks. Inspired by the classical concept of turnpike, we…

AI Foundation Model for Time Series with Innovations Representation
Lang Tong, Xinyi Wang
https://arxiv.org/abs/2510.01560 https://arxiv.org/pdf/2510.01560…

AI Foundation Model for Time Series with Innovations Representation
This paper introduces an Artificial Intelligence (AI) foundation model for time series in engineering applications, where causal operations are required for real-time monitoring and control. Since engineering time series are governed by physical, rather than linguistic, laws, large-language-model-based AI foundation models may be ineffective or inefficient. Building on the classical innovations representation theory of Wiener, Kallianpur, and Rosenblatt, we propose Time Series GPT (TS-GPT) -- a…

Dispersion Formation Control: from Geometry to Distribution
Jin Chen, Jesus Bautista Villar, Bayu Jayawardhana, Hector Garcia de Marina
https://arxiv.org/abs/2509.19784 https://…

Dispersion Formation Control: from Geometry to Distribution
We introduce and develop the concept of dispersion formation control, bridging a gap between shape-assembly studies in physics and biology and formation control theory. In current formation control studies, the control objectives typically focus on achieving desired local geometric properties, such as inter-agent distances, bearings, or relative positions. In contrast, our dispersion formation control approach enables agents to directly regulate the dispersion of their spatial distribution, a g…

Crosslisted article(s) found for eess.SP. https://arxiv.org/list/eess.SP/new
[1/1]:
- A Control Theory inspired Exploration Method for a Linear Bandit driven by a Linear Gaussian Dyna...
Jonathan Gornet, Yilin Mo, Bruno Sinopoli

Efficient Optimal Path Planning in Dynamic Environments Using Koopman MPC
Mohammad Abtahi, Navid Mojahed, Shima Nazari
https://arxiv.org/abs/2510.02584 https://

Efficient Optimal Path Planning in Dynamic Environments Using Koopman MPC
This paper presents a data-driven model predictive control framework for mobile robots navigating in dynamic environments, leveraging Koopman operator theory. Unlike the conventional Koopman-based approaches that focus on the linearization of system dynamics only, our work focuses on finding a global linear representation for the optimal path planning problem that includes both the nonlinear robot dynamics and collision-avoidance constraints. We deploy extended dynamic mode decomposition to ide…

Theory of Multi-photon Processes for Applications in Quantum Control
Longxiang Huang, Jacquelin Luneau, Johannes Schirk, Florian Wallner, Christian M. F. Schneider, Stefan Filipp, Klaus Liegener, Peter Rabl
https://arxiv.org/abs/2509.16074

Theory of Multi-photon Processes for Applications in Quantum Control
We present a general theoretical framework for evaluating multi-photon processes in periodically driven quantum systems, which have been identified as a versatile tool for engineering and controlling nontrivial interactions in various quantum technology platforms. To achieve the accuracy required for such applications, the resulting effective coupling rates, as well as any drive-induced frequency shifts, must be determined with very high precision. Here, we employ degenerate Floquet perturbatio…

A Crime/S.I.R. optimal control problem
Mariana \'Alvarez, Alexander Alegr\'ia, Andr\'es Rivera, Sebasti\'an Pedersen
https://arxiv.org/abs/2509.21406 https://

A Crime/S.I.R. optimal control problem
This paper presents and discusses a mathematical model inspired by control theory to derive optimal public policies for minimizing costs associated with the reduction and control of criminal activity in a population. Specifically, we analyze the optimal control problem \begin{equation*} \min G(u_1, u_2, u_3) = \int_{0}^{t_{\text{F}}} \left( I(t) - R(t) + \frac{B_1}{2} u_1^2(t) + \frac{B_2}{2} u_2^2(t) + \frac{B_3}{2} u_3^2(t) \right) \, dt. \end{equation*} where $I=I(t)$ and $R=R(t)$ satisfies …

Electromagnetically driven, environmentally adaptive, and functionally switchable hydrodynamic devices
Chen-Long Wu, Bin Wang, Hao Wang, Neng-Zhi Yao, Liujun Xu, Xuesheng Wang, Jiping Huang
https://arxiv.org/abs/2509.26491

Electromagnetically driven, environmentally adaptive, and functionally switchable hydrodynamic devices
Metamaterials provide exceptional control over physical phenomena, enabling many disruptive technologies. However, researches in hydrodynamic meta-devices have mainly used intrusive methods to manipulate material structures, limited by material properties and specific environmental conditions. Each design serves a single function, reducing versatility. This study introduces a meta-hydrodynamics theory using applied force fields to avoid physical contact with the fluid and eliminate the need for…

Invariant Price of Anarchy: a Metric for Welfarist Traffic Control
Ilia Shilov, Mingjia He, Heinrich H. Nax, Emilio Frazzoli, Gioele Zardini, Saverio Bolognani
https://arxiv.org/abs/2512.05843 https://arxiv.org/pdf/2512.05843 https://arxiv.org/html/2512.05843
arXiv:2512.05843v1 Announce Type: new
Abstract: The Price of Anarchy (PoA) is a standard metric for quantifying inefficiency in socio-technical systems, widely used to guide policies like traffic tolling. Conventional PoA analysis relies on exact numerical costs. However, in many settings, costs represent agents' preferences and may be defined only up to possibly arbitrary scaling and shifting, representing informational and modeling ambiguities. We observe that while such transformations preserve equilibrium and optimal outcomes, they change the PoA value. To resolve this issue, we rely on results from Social Choice Theory and define the Invariant PoA. By connecting admissible transformations to degrees of comparability of agents' costs, we derive the specific social welfare functions which ensure that efficiency evaluations do not depend on arbitrary rescalings or translations of individual costs. Case studies on a toy example and the Zurich network demonstrate that identical tolling strategies can lead to substantially different efficiency estimates depending on the assumed comparability. Our framework thus demonstrates that explicit axiomatic foundations are necessary in order to define efficiency metrics and to appropriately guide policy in large-scale infrastructure design robustly and effectively.
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Probability Density Estimation via Optimal Control
Markus Hegland, C. Yal\c{c}{\i}n Kaya
https://arxiv.org/abs/2510.00835 https://arxiv.org/pdf/2510.00835

Probability Density Estimation via Optimal Control
We employ optimal control theory to study the problem of estimating the probability density function from a data set originating from an unknown probability distribution. The original variational problem is reformulated as a multi-stage optimal control problem and the associated maximum principle, or conditions of optimality, is reduced to a two-point boundary-value problem with interior conditions. A numerical scheme is proposed to solve the discretization of this problem. Estimates of density…

A High-Frequency Uncertainty Principle for the Fourier-Bessel Transform
Benjamin Jaye, Rahul Sethi
https://arxiv.org/abs/2509.25500 https://arxiv.org/pdf/2…

A High-Frequency Uncertainty Principle for the Fourier-Bessel Transform
Motivated by problems in control theory concerning decay rates for the damped wave equation $$w_{tt}(x,t) + γ(x) w_t(x,t) + (-Δ+ 1)^{s/2} w(x,t) = 0,$$ we consider an analogue of the classical Paneah-Logvinenko-Sereda theorem for the Fourier Bessel transform. In particular, if $E \subset \mathbb{R}^+$ is $μ_α$-relatively dense (where $dμ_α(x) \approx x^{2α+1}\, dx$) for $α> -1/2$, and $\operatorname{supp} \mathcal{F}_α(f) \subset [R,R+1]$, then we show $$\|f\|_{L^2_α(\mathbb…

A Control Theory inspired Exploration Method for a Linear Bandit driven by a Linear Gaussian Dynamical System
Jonathan Gornet, Yilin Mo, Bruno Sinopoli
https://arxiv.org/abs/2510.01364

A Control Theory inspired Exploration Method for a Linear Bandit driven by a Linear Gaussian Dynamical System
The paper introduces a linear bandit environment where the reward is the output of a known Linear Gaussian Dynamical System (LGDS). In this environment, we address the fundamental challenge of balancing exploration -- gathering information about the environment -- and exploitation -- selecting to the action with the highest predicted reward. We propose two algorithms, Kalman filter Upper Confidence Bound (Kalman-UCB) and Information filter Directed Exploration Action-selection (IDEA). Kalman-UC…

Hamilton--Jacobi--Bellman equation for optimal control of stochastic Wasserstein--Hamiltonian system on graphs
Jianbo Cui, Tonghe Dang
https://arxiv.org/abs/2509.25965 https://

Hamilton--Jacobi--Bellman equation for optimal control of stochastic Wasserstein--Hamiltonian system on graphs
Stochastic optimal control problems for Hamiltonian dynamics on graphs have wide-ranging applications in mechanics and quantum field theory, particularly in systems with graph-based structures. In this paper, we establish the existence and uniqueness of viscosity solutions for a new class of Hamilton--Jacobi--Bellman (HJB) equations arising from the optimal control of stochastic Wasserstein--Hamiltonian systems (SWHSs) on graphs. One distinctive feature of these HJB equations is the simultaneou…

Crosslisted article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- Leveraging the group structure of hypotheses for more powerful multiple testing with FDR control ...
Marina Bogomolov, Shinjini Nandi

Generalized Beyond-Diagonal RIS Architectures: Theory and Design via Structure-oriented Symmetric Unitary Projection
Xiaohua Zhou, Tianyu Fang, Yijie Mao, Bruno Clerckx
https://arxiv.org/abs/2509.17804

Generalized Beyond-Diagonal RIS Architectures: Theory and Design via Structure-oriented Symmetric Unitary Projection
Beyond-diagonal reconfigurable intelligent surface (BD-RIS), which enables advanced wave control through interconnection of RIS elements, are gaining growing recognition as a promising technology for 6G and beyond. However, the enhanced flexibility of BD-RIS in controlling the phase and amplitude of reflected signals comes at the cost of high circuit complexity. In this paper, we propose two novel BD-RIS architectures, namely, the stem-connected RIS and cluster-connected RIS, to explore trade-o…

Refine coherent control of atomic qubits via wave-function approach conditioned on no-decay
Yuan Sun
https://arxiv.org/abs/2509.20042 https://arxiv.org/pdf…

Refine coherent control of atomic qubits via wave-function approach conditioned on no-decay
As a fundamental phenomenon in quantum systems, spontaneous emission constitutes an inevitable source of error, which ultimately degrades the fidelity of quantum logic gates. A successful quantum logic gate needs to operate on the condition that no decay event, such as spontaneous emission, occurs. Such successes can be ensured by post-selection based on syndrome extraction according to the theory of quantum error correction or quantum error mitigation. In this case, the wave function of qubits…

Crosslisted article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Feedback Control for Small Budget Pacing
Sreeja Apparaju, Yichuan Niu, Xixi Qi
h…

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, …

Limit theory for mean-field control problems with common noise adapted controls
Bruno Bouchard, Xiaolu Tan
https://arxiv.org/abs/2509.14734 https://arxiv.o…

Limit theory for mean-field control problems with common noise adapted controls
We consider a mean-field control problem in which admissible controls are required to be adapted to the common noise filtration. The main objective is to show how the mean-field control problem can be approximates by time consistent centralized finite population problems in which the central planner has full information on all agents' states and gives an identical signal to all agents. We also aim at establishing the optimal convergence rate. In a first general path-dependent setting, we only p…

Optimized Control of Duplex Networks
Haoyu Zheng, Xizhe Zhang
https://arxiv.org/abs/2509.21767 https://arxiv.org/pdf/2509.21767

Optimized Control of Duplex Networks
Many real-world complex systems can be modeled as multiplex networks, where each layer represents a distinct set of interactions among the same entities. Controlling such systems-steering them toward desired states using external inputs-is crucial across many domains. However, existing network control theory largely focuses on single-layer networks, and applying separate controls to each layer of a multiplex system often leads to redundant sets of driver nodes, increasing cost and complexity. …

Large-Scale Self-Powered Vibration Control: Theory and Experiment
Connor Ligeikis, Heath Hofmann, Jeff Scruggs
https://arxiv.org/abs/2509.11346 https://arx…

Large-Scale Self-Powered Vibration Control: Theory and Experiment
A self-powered system is a control technology that powers itself by harvesting energy from exogenous disturbances. This article details the design and experimental validation of a prototype self-powered vibration control system, for larger-scale applications (i.e., power flows above 1W and forces on the order of 1kN.) The prototype consists of a linear ballscrew coupled with a permanent-magnet synchronous machine. A custom three-phase inverter is used to control power flow, and a custom half-br…

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…

A Fast Initialization Method for Neural Network Controllers: A Case Study of Image-based Visual Servoing Control for the multicopter Interception
Chenxu Ke, Congling Tian, Kaichen Xu, Ye Li, Lingcong Bao
https://arxiv.org/abs/2509.19110

Twist-modulated magnetic interactions in bilayer van der Waals materials
Tomas T. Osterholt, D. O. Oriekhov, Lumen Eek, Cristiane Morais Smith, Rembert A. Duine
https://arxiv.org/abs/2509.14122

Twist-modulated magnetic interactions in bilayer van der Waals materials
The ability to control magnetic interactions at the nanoscale is crucial for the development of next-generation spintronic devices and functional magnetic materials. In this work, we investigate theoretically, by means of many-body perturbation theory, how interlayer twisting modulates magnetic interactions in bilayer van der Waals systems composed of two ferromagnetic layers. We demonstrate that the relative strengths of the interlayer Heisenberg exchange interaction, the Dzyaloshinskii-Moriya…

Sampling Method for Generalized Graph Signals with Pre-selected Vertices via DC Optimization
Keitaro Yamashita, Kazuki Naganuma, Shunsuke Ono
https://arxiv.org/abs/2509.14836 ht…

Sampling Method for Generalized Graph Signals with Pre-selected Vertices via DC Optimization
This paper proposes a method for vertex-wise flexible sampling of a broad class of graph signals, designed to attain the best possible recovery based on the generalized sampling theory. This is achieved by designing a sampling operator by an optimization problem, which is inherently non-convex, as the best possible recovery imposes a rank constraint. An existing method for vertex-wise flexible sampling is able to control the number of active vertices but cannot incorporate prior knowledge of ma…

Observation of topological Phenomena in a Weyl Exceptional Ring with Single Photons
Zhong-Sheng Chen, Wei-Xin Chen, Fan Wu, Zhong-Wei Xu, Jing Ma, Yun-Kun Jiang, Huai-Zhi Wu, Shi-Biao Zheng
https://arxiv.org/abs/2509.13708

Observation of topological Phenomena in a Weyl Exceptional Ring with Single Photons
Compared with Hermitian theory, non-Hermitian physics offers a fundamentally different mathematical framework, enabling the observation of topological phenomena that have no analogue in Hermitian systems. Among these, the exceptional point (EP) ring stands out as a quintessential topological feature unique to non-Hermitian systems. In this study, we employ single-photon interferometry to overcome the experimental challenge of precise phase control in quantum systems, thereby enabling a complete…

Revealing Chaotic Dependence and Degree-Structure Mechanisms in Optimal Pinning Control of Complex Networks
Qingyang Liu (University of Science and Technology of China), Tianlong Fan (University of Science and Technology of China), Liming Pan (University of Science and Technology of China), Linyuan Lv (University of Science and Technology of China)
https://

Revealing Chaotic Dependence and Degree-Structure Mechanisms in Optimal Pinning Control of Complex Networks
Identifying an optimal set of driver nodes to achieve synchronization via pinning control is a fundamental challenge in complex network science, limited by computational intractability and the lack of general theory. Here, leveraging a degree-based mean-field (annealed) approximation from statistical physics, we analytically reveal how the structural degree distribution systematically governs synchronization performance, and derive an analytic characterization of the globally optimal pinning se…

Implicit Third-Order Peer Triplets with Variable Stepsizes for Gradient-Based Solutions in Large-Scale ODE-Constrained Optimal Control
Jens Lang, Bernhard A. Schmitt
https://arxiv.org/abs/2509.11684

Implicit Third-Order Peer Triplets with Variable Stepsizes for Gradient-Based Solutions in Large-Scale ODE-Constrained Optimal Control
This paper is concerned with the theory, construction and application of variable-stepsize implicit Peer two-step methods that are super-convergent for variable stepsizes, i.e., preserve their classical order achieved for uniform stepsizes when applied in a gradient-based solution algorithm to solve ODE-constrained optimal control problems in a first-discretize-then-optimize setting. Gradients of the objective function can be computed most efficiently using approximate adjoint variables. High a…

Koopman-Operator-Based Model Predictive Control for Drag-free Satellite
Yankai Wang, Ti Chen
https://arxiv.org/abs/2509.20100 https://arxiv.org/pdf/2509.20…

Koopman-Operator-Based Model Predictive Control for Drag-free Satellite
This paper presents a data-driven modelling method for nonlinear dynamics of drag-free satellite based on Koopman operator theory, and a model predictive controller is designed based on the identified model. The nonlinear dynamics of drag-free satellite are identified and controlled based on Sparse Identification of Nonlinear Dynamics (SINDy). Using the manually constructed nonlinear function dictionary as observables, the system approximation is obtained by SINDy algorithm, and a linear Model …

Uniform Sampling from the Reachable Set Using Optimal Transport
Karthik Elamvazhuthi, Sachin Shivakumar
https://arxiv.org/abs/2509.15571 https://arxiv.org/…

Uniform Sampling from the Reachable Set Using Optimal Transport
Finding the reachable set of a system has a wide range of applications, but is a fundamental challenge in control theory, especially when controls are bounded. Although one can simply integrate the system samples forward in time by applying random admissible control to approximate the reachable set, the samples typically cluster near an attractor (if one is present) -- yielding a poor representation of the reachable set. A better representation can be found by applying controls that specificall…

Dissipativity-Based Data-Driven Decentralized Control of Interconnected Systems
Taiki Nakano, Ahmed Aboudonia, Jaap Eising, Andrea Martinelli, Florian D\"orfler, John Lygeros
https://arxiv.org/abs/2509.14047

Dissipativity-Based Data-Driven Decentralized Control of Interconnected Systems
We propose data-driven decentralized control algorithms for stabilizing interconnected systems. We first derive a data-driven condition to synthesize a local controller that ensures the dissipativity of the local subsystems. Then, we propose data-driven decentralized stability conditions for the global system based on the dissipativity of each local system. Since both conditions take the form of linear matrix inequalities and are based on dissipativity theory, this yields a unified pipeline, re…

Crosslisted article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- A Recovery Theory for Diffusion Priors: Deterministic Analysis of the Implicit Prior Algorithm
Oscar Leong, Yann Traonmilin

Automated Algorithm Design via Nevanlinna-Pick Interpolation
Ibrahim K. Ozaslan, Tryphon T. Georgiou, Mihailo R. Jovanovic
https://arxiv.org/abs/2509.21416 https://

Automated Algorithm Design via Nevanlinna-Pick Interpolation
The synthesis of optimization algorithms typically follows a design-first-analyze-later approach, which often obscures fundamental performance limitations and hinders the systematic design of algorithms operating at the achievable theoretical boundaries. Recently, a framework based on frequency-domain techniques from robust control theory has emerged as a powerful tool for automating algorithm synthesis. By integrating the design and analysis stages, this framework enables the identification of…

Replaced article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- A Universal Birkhoff Theory for Fast Trajectory Optimization
I. M. Ross
https…

Lyndon Word Transduction to Improve the Efficiency of Computing Chen-Fliess Series
W. Steven Gray, Fatima Raza, Lance Berlin, Luis A. Duffaut Espinosa
https://arxiv.org/abs/2509.19908

Lyndon Word Transduction to Improve the Efficiency of Computing Chen-Fliess Series
The class of input-output systems representable as Chen-Fliess series arises often in control theory. One well known drawback of this representation, however, is that the iterated integrals which appear in these series are algebraically related by the shuffle product. This becomes relevant when one wants to numerically evaluate these series in applications, as this redundancy leads to unnecessary computational expense. The general goal of this paper is to present a computationally efficient way…

Automated algorithm design for convex optimization problems with linear equality constraints
Ibrahim K. Ozaslan, Wuwei Wu, Jie Chen, Tryphon T. Georgiou, Mihailo R. Jovanovic
https://arxiv.org/abs/2509.20746

Automated algorithm design for convex optimization problems with linear equality constraints
Synthesis of optimization algorithms typically follows a {\em design-then-analyze\/} approach, which can obscure fundamental performance limits and hinder the systematic development of algorithms that operate near these limits. Recently, a framework grounded in robust control theory has emerged as a powerful tool for automating algorithm synthesis. By integrating design and analysis stages, fundamental performance bounds are revealed and synthesis of algorithms that achieve them is enabled. In …

Bellman Optimality of Average-Reward Robust Markov Decision Processes with a Constant Gain
Shengbo Wang, Nian Si
https://arxiv.org/abs/2509.14203 https://a…

Bellman Optimality of Average-Reward Robust Markov Decision Processes with a Constant Gain
Learning and optimal control under robust Markov decision processes (MDPs) have received increasing attention, yet most existing theory, algorithms, and applications focus on finite-horizon or discounted models. The average-reward formulation, while natural in many operations research and management contexts, remains underexplored. This is primarily because the dynamic programming foundations are technically challenging and only partially understood, with several fundamental questions remaining…

Accelerated Gradient Methods with Biased Gradient Estimates: Risk Sensitivity, High-Probability Guarantees, and Large Deviation Bounds
Mert G\"urb\"uzbalaban, Yasa Syed, Necdet Serhat Aybat
https://arxiv.org/abs/2509.13628

Accelerated Gradient Methods with Biased Gradient Estimates: Risk Sensitivity, High-Probability Guarantees, and Large Deviation Bounds
We study trade-offs between convergence rate and robustness to gradient errors in first-order methods. Our focus is on generalized momentum methods (GMMs), a class that includes Nesterov's accelerated gradient, heavy-ball, and gradient descent. We allow stochastic gradient errors that may be adversarial and biased, and quantify robustness via the risk-sensitive index (RSI) from robust control theory. For quadratic objectives with i.i.d. Gaussian noise, we give closed-form expressions for RSI us…