Tootfinder

Panthers likely to ditch RB shuffle, go with Dowdle https://www.espn.com/nfl/story/_/id/46747517/panthers-likely-give-heavier-workload-rico-dowdle

Rezension: Alternative Defence Review https://www.german-foreign-policy.com/news/detail/10245

Es geht los!
Das neue »European Digital Infrastructure Consortium« (#EDIC) für Digital Commons startet am 11. Dezember mit einer Auftaktveranstaltung in Den Haag. 🙌 🚀
Ziele:
· Offene Alternativen in digitalen Schlüsselbereichen fördern
· Stärkung des #europ. digitalen Ökosystems
…

Digitale Stärke zurückgewinnen
Frankreich, Deutschland, die Niederlande und Italien gründen ein Konsortium für Digitale Gemeingüter

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.
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Closed-loop control of sloshing fuel in a spinning spacecraft
Umberto Zucchelli, Miguel Alfonso Mendez, Annafederica Urbano, Sebastien Vincent-Bonnieu, Piotr Wenderski, Francesco Sanfedino
https://arxiv.org/abs/2510.08121

Closed-loop control of sloshing fuel in a spinning spacecraft
New-generation space missions require satellites to carry substantial amounts of liquid propellant, making it essential to analyse the coupled control-structure-propellant dynamics in detail. While Computational Fluid Dynamics (CFD) offers high-fidelity predictions, its computational cost limits its use in iterative design. Equivalent Mechanical Models (EMMs) provide a faster alternative, though their predictive performance, especially in closed-loop scenarios, remains largely unexplored. This …