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In a paper by Willems and coauthors it was shown that persistently exciting data can be used to represent the input-output behavior of a linear system. Based on this fundamental result, we derive a parametrization of linear feedback systems…

Systems and Control · Computer Science 2019-09-10 Claudio De Persis , Pietro Tesi

The paper presents a model reduction framework geared towards the analysis and design of systems that switch and oscillate. While such phenomena are ubiquitous in nature and engineering, model reduction methods are not well developed for…

Systems and Control · Electrical Eng. & Systems 2020-05-19 Alberto Padoan , Fulvio Forni , Rodolphe Sepulchre

Stabilization of non-stationary linear systems over noisy communication channels is considered. Stochastically stable sources, and unstable but noise-free or bounded-noise systems have been extensively studied in information theory and…

Information Theory · Computer Science 2012-05-07 Serdar Yüksel

Predictive control, which is based on a model of the system to compute the applied input optimizing the future system behavior, is by now widely used. If the nominal models are not given or are very uncertain, data-driven model predictive…

Systems and Control · Electrical Eng. & Systems 2023-03-09 Hoang Hai Nguyen , Maurice Friedel , Rolf Findeisen

In this paper, we study the control of a class of time-invariant linear ensemble systems whose natural dynamics are linear in the system parameter. This class of ensemble control systems arises from practical engineering and physical…

Optimization and Control · Mathematics 2014-10-07 Jr-Shin Li , Ji Qi

Various controllability conditions have been obtained by researchers for heterogeneous networked systems with linear dynamics. However, the literature for nonlinear, heterogeneous networked systems is comparatively less. In this paper we…

Optimization and Control · Mathematics 2024-12-18 Aleena Thomas , Abhijith Ajayakumar , Raju K. George

This paper considers data rate limitations for mean square stabilization of uncertain discrete-time linear systems via finite data rate and lossy channels. For a plant having parametric uncertainties, a necessary condition and a sufficient…

Systems and Control · Computer Science 2012-02-22 Kunihisa Okano , Hideaki Ishii

This paper addresses the analysis of a boundary feedback system involving a non-homogeneous Euler-Bernoulli beam governed by the equation $m(x)u_{tt}+\mu(x)u_{t}$$+\left(r(x)u_{xx}\right)_{xx}=0$, subject to the initial $u(x,0)=u_0(x)$,…

Optimization and Control · Mathematics 2023-07-06 Alemdar Hasanov

This paper applies the classical prediction error method (PEM) to the estimation of nonlinear discrete-time models of neuronal systems subject to input-additive noise. While the nonlinear system exhibits excitability, bifurcations, and…

Systems and Control · Electrical Eng. & Systems 2024-02-19 Thiago B. Burghi , Maarten Schoukens , Rodolphe Sepulchre

This paper presents a systematic approach to the design of a robust dynamic state feedback controller using copies of the plant nonlinearities, which is based on the use of IQCs and minimax LQR control. The approach combines a linear state…

Systems and Control · Computer Science 2014-04-16 Obaid Ur Rehman , Ian R. Petersen

This paper studies the stochastic optimal control problem for systems with unknown dynamics. First, an open-loop deterministic trajectory optimization problem is solved without knowing the explicit form of the dynamical system. Next, a…

Systems and Control · Computer Science 2017-05-30 Dan Yu , Mohammadhussein Rafieisakhaei , Suman Chakravorty

The theory of controlled mechanical systems of [6, 3, 4] is extended to the case of ideal incompressible fluids consisting of charged particles in the presence of an external magnetic field. The resulting control is of feedback type and…

Mathematical Physics · Physics 2021-03-10 Simon Hochgerner

This work studies the design of safe control policies for large-scale non-linear systems operating in uncertain environments. In such a case, the robust control framework is a principled approach to safety that aims to maximize the…

Systems and Control · Computer Science 2019-03-04 Edouard Leurent , Yann Blanco , Denis Efimov , Odalric-Ambrym Maillard

Modern nonlinear control theory seeks to endow systems with properties such as stability and safety, and has been deployed successfully across various domains. Despite this success, model uncertainty remains a significant challenge in…

Systems and Control · Electrical Eng. & Systems 2021-04-02 Andrew J. Taylor , Victor D. Dorobantu , Sarah Dean , Benjamin Recht , Yisong Yue , Aaron D. Ames

We present a framework for learning of modeling uncertainties in Linear Time Invariant (LTI) systems. We propose a methodology to extend the dynamics of an LTI (without uncertainty) with an uncertainty model, based on measured data, to…

Systems and Control · Electrical Eng. & Systems 2023-11-01 Farhad Ghanipoor , Carlos Murguia , Peyman Mohajerin Esfahani , Nathan van de Wouw

Control using quantized feedback is a fundamental approach to system synthesis with limited communication capacity. In this paper, we address the stabilization problem for unknown linear systems with logarithmically quantized feedback, via…

Optimization and Control · Mathematics 2022-03-11 Feiran Zhao , Xingchen Li , Keyou You

This paper focuses on the invariance control problem for discrete-time switched nonlinear systems. The proposed approach computes controlled invariant sets in a finite number of iterations and directly yields a partition-based invariance…

Optimization and Control · Mathematics 2016-09-01 Yinan Li , Jun Liu

A mathematical model of a simply supported Euler-Bernoulli beam with attached spring-mass system is considered. The model is controlled by distributed piezo actuators and lumped force. We address the issue of asymptotic behavior of…

Optimization and Control · Mathematics 2022-08-09 Julia Kalosha , Alexander Zuyev

This paper considers the relaxed version of the transport problem for general nonlinear control systems, where the objective is to design time-varying feedback laws that transport a given initial probability measure to a target probability…

Systems and Control · Computer Science 2018-07-27 Karthik Elamvazhuthi , Piyush Grover , Spring Berman

This paper deals with the stochastic control of nonlinear systems in the presence of state and control constraints, for uncertain discrete-time dynamics in finite dimensional spaces. In the deterministic case, the viability kernel is known…

Optimization and Control · Mathematics 2010-02-08 Luc Doyen , Delara Michel
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