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We investigate the stabilisation of nominally linear-affine switched systems with uncertain Lipschitz nonlinearities under dwell-time constraints, using a sampled-data switching law based on a state observer. We design the switching law…

Optimization and Control · Mathematics 2026-04-29 Rami Katz , Antonio Russo , Gian Paolo Incremona , Patrizio Colaneri , Giulia Giordano

We develop a linear systems theory that coincides with the existing theories for continuous and discrete dynamical systems, but that also extends to linear systems defined on nonuniform time domains. The approach here is based on…

Optimization and Control · Mathematics 2009-03-03 John M. Davis , Ian A. Gravagne , Billy J. Jackson , Robert J. Marks

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

We study the stability properties of linear time-varying systems in continuous time whose system matrix is Metzler with zero row sums. This class of systems arises naturally in the context of distributed decision problems, coordination and…

Optimization and Control · Mathematics 2007-05-23 Luc Moreau

We propose a certainty-equivalence scheme for adaptive control of scalar linear systems subject to additive, i.i.d. Gaussian disturbances and bounded control input constraints, without requiring prior knowledge of the bounds of the system…

Systems and Control · Electrical Eng. & Systems 2023-03-20 Seth Siriya , Jingge Zhu , Dragan Nešić , Ye Pu

Machine-learning technologies for learning dynamical systems from data play an important role in engineering design. This research focuses on learning continuous linear models from data. Stability, a key feature of dynamic systems, is…

Machine Learning · Computer Science 2023-01-25 Pawan Goyal , Igor Pontes Duff , Peter Benner

This paper derives two stabilizability theorems for a basic class of discrete-time nonlinear systems with multiple unknown parameters. First, we claim that a discrete-time multi-parameter system is stabilizable if its nonlinear growth rate…

Optimization and Control · Mathematics 2020-07-23 Zhaobo Liu , Chanying Li

In this paper, a sampling-based Stochastic Model Predictive Control algorithm is proposed for discrete-time linear systems subject to both parametric uncertainties and additive disturbances. One of the main drivers for the development of…

In this paper we consider output controllability for linear time-invariant systems. In a recent paper by Danhane, Loh{\'e}ac and Jungers it has been pointed out that although output controllability is a classical notion in control theory,…

Optimization and Control · Mathematics 2023-06-16 Michael Schönlein

This paper studies robustness of MIMO control systems with parametric uncertainties, and establishes a lower dimensional robust stability criterion. For control systems with interval transfer matrices, we identify the minimal testing set…

Statistics Theory · Mathematics 2007-06-13 Long Wang

An eigenvalue based framework is developed for the stability analysis and stabilization of coupled systems with time-delays, which are naturally described by delay differential algebraic equations. The spectral properties of these equations…

Systems and Control · Electrical Eng. & Systems 2020-03-26 Wim Michiels , Suat Gumussoy

This paper studies the problem of stabilization of a nonlinear system with time-varying delays in both sensing and actuation using event-triggered control. Our proposed strategy seeks to opportunistically minimize the number of control…

Systems and Control · Computer Science 2020-01-14 Erfan Nozari , Pavankumar Tallapragada , Jorge Cortés

Predictor-based stabilization results are provided for nonlinear systems with input delays and a compact absorbing set. The control scheme consists of an inter-sample predictor, a global observer, an approximate predictor, and a nominal…

Optimization and Control · Mathematics 2013-06-17 Iasson Karafyllis , Miroslav Krstic , Tarek Ahmed-Ali , Francoise Lamnabhi-Lagarrigue

In this paper, we consider optimal control problems derived by stochastic systems with delay, where control domains are non-convex and the diffusion coefficients depend on control variables. By an estimate of the integral of…

Optimization and Control · Mathematics 2022-10-25 Qixia Zhang

In this paper, we develop and analyze an integral fixed-time sliding mode control method for a scenario in which the system model is only partially known, utilizing Gaussian processes. We present two theorems on fixed-time convergence. The…

Systems and Control · Electrical Eng. & Systems 2025-05-30 Chaimae El Mortajinea , Moussa Labbadib , Adnane Saoudc , Mostafa Bouzia

We consider stability analysis of constrained switching linear systems in which the dynamics is unknown and whose switching signal is constrained by an automaton. We propose a data-driven Lyapunov framework for providing probabilistic…

Systems and Control · Electrical Eng. & Systems 2022-07-15 Adrien Banse , Zheming Wang , Raphaël M. Jungers

Spatiotemporal chaos (STC) exhibited by the Kuramoto-Sivashinsky (KS) equation is investigated analytically and numerically. An effective stochastic equation belonging to the KPZ universality class is constructed by incorporating the…

Condensed Matter · Physics 2015-06-25 Carson C. Chow , Terence Hwa

The problem of p-th moment stability for time-varying stochastic time-delay systems with Markovian switching is investigated in this paper. Some novel stability criteria are obtained by applying the generalized Razumikhin and Krasovskii…

Dynamical Systems · Mathematics 2016-07-11 Bin Zhou , Weiwei Luo

Two nested classes of discrete-time linear time-invariant systems, which differ by the set of periodic signals that they leave invariant, are studied. The first class preserves the property of periodic monotonicity (period-wise…

Optimization and Control · Mathematics 2026-02-10 Christian Grussler

We present a straightforward and efficient way to control unstable robotic systems using an estimated dynamics model. Specifically, we show how to exploit the differentiability of Gaussian Processes to create a state-dependent linearized…

Robotics · Computer Science 2021-08-03 Ivan D. Jimenez Rodriguez , Ugo Rosolia , Aaron D. Ames , Yisong Yue
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