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In this paper we propose a robust Model Predictive Control where a Gated Recurrent Unit network model is used to learn the input-output dynamic of the system under control. Robust satisfaction of input and output constraints and recursive…

Systems and Control · Electrical Eng. & Systems 2023-12-20 Irene Schimperna , Lalo Magni

In this thesis, we provide an initial investigation into bounds for topological entropy of switched linear systems. Entropy measures, roughly, the information needed to describe the behavior of a system with finite precision on finite time…

Optimization and Control · Mathematics 2016-10-14 James Schmidt

This paper addresses the distributed online control problem over a network of linear time-invariant (LTI) systems (with possibly unknown dynamics) in the presence of adversarial perturbations. There exists a global network cost that is…

Optimization and Control · Mathematics 2023-10-06 Ting-Jui Chang , Shahin Shahrampour

One of the most important branches of nonlinear control theory is the so-called sliding-mode. Its aim is the design of a (nonlinear) feedback law that brings and maintains the state trajectory of a dynamic system on a given sliding surface.…

Systems and Control · Electrical Eng. & Systems 2021-09-14 Mauro Bisiacco , Gianluigi Pillonetto

We introduce the concept of a control contraction metric, extending contraction analysis to constructive nonlinear control design. We derive sufficient conditions for exponential stabilizability of all trajectories of a nonlinear control…

Systems and Control · Computer Science 2017-02-09 Ian R. Manchester , Jean-Jacques E. Slotine

This paper presents an adaptive control framework for Euler-Lagrange (E-L) systems that enforces user-defined time-varying state and input constraints in the presence of parametric uncertainties and bounded disturbances. The proposed design…

Systems and Control · Electrical Eng. & Systems 2026-03-10 Poulomee Ghosh , Shubhendu Bhasin

This paper studies a fundamental relation that exists between stabilizability assumptions usually employed in distributed model predictive control implementations, and the corresponding notions of invariance implicit in such controllers.…

Systems and Control · Computer Science 2016-11-03 Bernardo Hernandez , Pablo Baldivieso , Paul Trodden

We address the problem of verifying closed-loop contraction in nonlinear control systems whose controller and contraction metric are both parameterized by neural networks. By leveraging interval analysis and interval bound propagation, we…

Systems and Control · Electrical Eng. & Systems 2025-12-03 Alexander Davydov

The paper is concerned with the boundary controllability of entropy weak solutions to hyperbolic systems of conservation laws. We prove a general result on the asymptotic stabilization of a system near a constant state. On the other hand,…

Optimization and Control · Mathematics 2007-05-23 Alberto Bressan , Giuseppe Maria Coclite

For a non-linear MIMO feedback system, the robustness against uncertain time-variations in the feedback loop is investigated in an input-output framework. A general sufficient condition in terms of a bound on average rates of time-variation…

Systems and Control · Electrical Eng. & Systems 2020-03-03 Yu-chen Sung , Sagar V. Patil , Michael G. Safonov

Practical adaptive control implementations where human pilots coexist in the loop are still uncommon, despite their success in handling uncertain dynamical systems. This is owing to their special nonlinear characteristics which lead to…

Systems and Control · Electrical Eng. & Systems 2022-08-30 Abdullah Habboush , Yildiray Yildiz

Online convex optimization (OCO) is a powerful tool for learning sequential data, making it ideal for high precision control applications where the disturbances are arbitrary and unknown in advance. However, the ability of OCO-based…

Systems and Control · Electrical Eng. & Systems 2024-05-14 Joyce Lai , Peter Seiler

Learning governing dynamics from data is a common goal across the sciences, yet it is only well-posed when the underlying mechanisms are identifiable. In practice, many data-driven methods implicitly assume identifiability; when this…

Machine Learning · Computer Science 2026-05-13 Aybüke Ulusarslan , Niki Kilbertus , Nora Schneider

This paper investigates the finite time stabilization problem for a class of nonlinear systems with unknown control directions and unstructured uncertainties. The unstructured uncertainties indicate that not only the parameters but also the…

Systems and Control · Electrical Eng. & Systems 2024-10-30 Shiqi Zheng , Shihao Wang , Xiang Chen , Yuanlong Xie

We consider a simple control problem in which the underlying dynamics depend on a parameter that is unknown and must be learned. We exhibit a control strategy which is optimal to within a multiplicative constant. While most authors find…

Optimization and Control · Mathematics 2021-09-15 Jacob Carruth , Maximilian F. Eggl , Charles Fefferman , Clarence W. Rowley , Melanie Weber

In this paper we consider the problem of a multi-agent system achieving a formation in the presence of misbehaving or adversarial agents. We introduce a novel continuous time resilient controller to guarantee that normally behaving agents…

Systems and Control · Computer Science 2021-06-11 James Usevitch , Kunal Garg , Dimitra Panagou

This paper investigates the robust asymptotic stabilization of a linear time-invariant (LTI) system by a static feedback with a static state quantization. It is shown that the controllable LTI system can be stabilized to zero in a finite…

Optimization and Control · Mathematics 2024-03-27 Yu Zhou , Andrey Polyakov , Gang Zheng

The stabilization of uncertain LTI/LPV time delay systems with time varying delays by state-feedback controllers is addressed. At the difference of other works in the literature, the proposed approach allows for the synthesis of resilient…

Systems and Control · Computer Science 2012-04-06 Corentin Briat , Olivier Sename , Jean-François Lafay

Time delayed feedback control is one of the most successful methods to discover dynamically unstable features of a dynamical system in an experiment. This approach feeds back only terms that depend on the difference between the current…

Dynamical Systems · Mathematics 2016-04-26 Jan Sieber

According to recent results, convergence in a prespecified or prescribed finite time can be achieved under extreme model uncertainty if control is applied continuously over time. This paper shows that this extreme amount of uncertainty…

Systems and Control · Electrical Eng. & Systems 2023-06-27 Hernan Haimovich , Rodrigo Aldana-Lopez , Richard Seeber , David Gomez-Gutierrez
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