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This paper is concerned with stability analysis of nonlinear time-varying systems by using Lyapunov function based approach. The classical Lyapunov stability theorems are generalized in the sense that the time-derivative of the Lyapunov…

Dynamical Systems · Mathematics 2017-08-18 Bin Zhou

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

Nonlinear dynamical systems are ubiquitous in nature and they are hard to forecast. Not only they may be sensitive to small perturbations in their initial conditions, but they are often composed of processes acting at multiple scales.…

Chaotic Dynamics · Physics 2025-10-06 Chenyu Dong , Davide Faranda , Adriano Gualandi , Valerio Lucarini , Gianmarco Mengaldo

For bilinear infinite-dimensional dynamical systems, we show the equivalence between uniform global asymptotic stability and integral input-to-state stability. We provide two proofs of this fact. One applies to general systems over Banach…

Dynamical Systems · Mathematics 2019-05-08 Andrii Mironchenko , Hiroshi Ito

In this paper, we develop a new approach to study gain operators built from the interconnection gains of infinite networks of dynamical systems. Our focus is on the construction of paths of strict decay which are used for building Lyapunov…

Optimization and Control · Mathematics 2021-12-14 Christoph Kawan , Majid Zamani

This paper proposes a data-driven framework to solve time-varying optimization problems associated with unknown linear dynamical systems. Making online control decisions to regulate a dynamical system to the solution of an optimization…

Optimization and Control · Mathematics 2021-09-08 Gianluca Bianchin , Miguel Vaquero , Jorge Cortes , Emiliano Dall'Anese

Controlling nonlinear stochastic dynamical systems involves substantial challenges when the dynamics contain unknown and unstructured nonlinear state-dependent terms. For such complex systems, deep neural networks can serve as powerful…

Systems and Control · Electrical Eng. & Systems 2024-12-31 Saiedeh Akbari , Cristian F. Nino , Omkar Sudhir Patil , Warren E. Dixon

This paper introduces a novel Lyapunov-based small-gain methodology for establishing fixed-time stability (FxTS) guarantees in interconnected dynamical systems. Specifically, we consider interconnections in which each subsystem admits an…

Systems and Control · Electrical Eng. & Systems 2025-12-01 Michael Tang , Miroslav Krstic , Jorge Poveda

This paper introduces a novel approach for achieving fixed-time tracking consensus control in multiagent systems (MASs). Departing from the reliance on traditional controllers, our innovative controller integrates modified tuning and…

Systems and Control · Electrical Eng. & Systems 2025-01-03 Kewei Zhou , Ziming Wang , Zhihao Chen , Xin Wang

This paper is devoted to two issues. One is to provide Lyapunov-based tools to establish integral input-to-state stability (iISS) and input-to-state stability (ISS) for some classes of nonlinear parabolic equations. The other is to provide…

Dynamical Systems · Mathematics 2014-10-14 Andrii Mironchenko , Hiroshi Ito

We explicitly construct global strict Lyapunov functions for rapidly time-varying nonlinear control systems. The Lyapunov functions we construct are expressed in terms of oftentimes more readily available Lyapunov functions for the limiting…

Optimization and Control · Mathematics 2007-05-23 Frederic Mazenc , Michael Malisoff , Marcio S. de Queiroz

In this paper we deal with infinite-dimensional nonlinear forward complete dynamical systems which are subject to external disturbances. We first extend the well-known Datko lemma to the framework of the considered class of systems. Thanks…

Optimization and Control · Mathematics 2020-02-18 Ihab Haidar , Yacine Chitour , Paolo Mason , Mario Sigalotti

We introduce a method for learning provably stable deep neural network based dynamic models from observed data. Specifically, we consider discrete-time stochastic dynamic models, as they are of particular interest in practical applications…

Machine Learning · Computer Science 2021-03-30 Nathan P. Lawrence , Philip D. Loewen , Michael G. Forbes , Johan U. Backström , R. Bhushan Gopaluni

We derive converse Lyapunov theorems for input-to-state stability (ISS) of linear infinite-dimensional analytic systems. We show that input-to-state stability of a linear system does not imply existence of a coercive quadratic ISS Lyapunov…

Optimization and Control · Mathematics 2025-09-19 Andrii Mironchenko , Felix Schwenninger

In this paper, we propose a data-driven approach for control of nonlinear dynamical systems. The proposed data-driven approach relies on transfer Koopman and Perron-Frobenius (P-F) operators for linear representation and control of such…

Systems and Control · Computer Science 2018-06-12 Apurba Kumar Das , Bowen Huang , Umesh Vaidya

This paper addresses the robust stability of a boundary controlled system coupling two partial differential equations (PDEs), namely beam and string equations, in the presence of boundary and in-domain disturbances under the framework of…

Analysis of PDEs · Mathematics 2018-11-19 Jun Zheng , Hugo Lhachemi , Guchuan Zhu , David Saussi

Dynamical systems theory has long provided a foundation for understanding evolving phenomena across scientific domains. Yet, the application of this theory to complex real-world systems remains challenging due to issues in mathematical…

Machine Learning · Computer Science 2024-11-05 Samuel A. Moore , Brian P. Mann , Boyuan Chen

This article concerns robustness analysis for interconnections of two dynamical systems (described by upper semicontinuous differential inclusions) using a generalized notion of derivatives associated with locally Lipschitz Lyapunov…

Optimization and Control · Mathematics 2021-10-19 Matteo Della Rossa , Aneel Tanwani , Luca Zaccarian

In this work we present further characterizations of integral input-to-state stability (iISS) for hybrid systems. In particular, the equivalence between 0-input uniform global asymptotic stability (0-UGAS) plus uniform bounded energy…

Systems and Control · Electrical Eng. & Systems 2023-11-22 Shenyu Liu , Antonio Russo

We propose a counter-example guided inductive synthesis (CEGIS) scheme for the design of control Lyapunov functions and associated state-feedback controllers for linear systems affected by parametric uncertainty with arbitrary shape. In the…

Systems and Control · Electrical Eng. & Systems 2024-07-09 Daniele Masti , Filippo Fabiani , Giorgio Gnecco , Alberto Bemporad