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Stabilizing controller design and region of attraction (RoA) estimation are essential in nonlinear control. Moreover, it is challenging to implement a control Lyapunov function (CLF) in practice when only partial knowledge of the system is…

Systems and Control · Electrical Eng. & Systems 2023-03-20 Shiqing Wei , Prashanth Krishnamurthy , Farshad Khorrami

We study asymptotic stability of continuous-time systems with mode-dependent guaranteed dwell time. These systems are reformulated as special cases of a general class of mixed (discrete-continuous) linear switching systems on graphs, in…

Dynamical Systems · Mathematics 2019-12-24 Yacine Chitour , Nicola Guglielmi , Mario Sigalotti , Vladimir Protasov

In this paper, by using a characterization of functions having fractional derivative, we propose a rigorous fractional Lyapunov function candidate method to analyze stability of fractional-order nonlinear systems. First, we prove an…

Classical Analysis and ODEs · Mathematics 2018-01-16 H. T. Tuan , Hieu Trinh

We consider constructing Lyapunov functions for systems that are both monotone and contractive with respect to a weighted one norm or infinity norm. This class of systems admits separable Lyapunov functions that are either the sum or the…

Systems and Control · Computer Science 2016-09-21 Samuel Coogan

Defining administrative workflow events as a nonlinear dynamics that assume a random ordered or disordered growth rate of information processing, a method has been proposed for large-scale administrative systems that structures hybrid…

Adaptation and Self-Organizing Systems · Physics 2019-10-21 Charles Roberto Telles

The stability analysis of possibly time varying positive semigroups on non necessarily compact state spaces, including Neumann and Dirichlet boundary conditions is a notoriously difficult subject. These crucial questions arise in a variety…

Probability · Mathematics 2023-04-18 Marc Arnaudon , Pierre Del Moral , El Maati Ouhabaz

Recent advances in learning-based control leverage deep function approximators, such as neural networks, to model the evolution of controlled dynamical systems over time. However, the problem of learning a dynamics model and a stabilizing…

Systems and Control · Electrical Eng. & Systems 2023-04-05 Youngjae Min , Spencer M. Richards , Navid Azizan

In addition to providing high-profile successes in computer vision and natural language processing, neural networks also provide an emerging set of techniques for scientific problems. Such data-driven models, however, typically ignore…

Computational Physics · Physics 2019-05-28 N. Benjamin Erichson , Michael Muehlebach , Michael W. Mahoney

The present paper is mainly aimed at introducing a novel notion of stability of nonlinear time-delay systems called Rational Stability. According to the Lyapunov-type, various sufficient conditions for rational stability are reached. Under…

Optimization and Control · Mathematics 2018-09-17 Nadhem Echi , Boulbaba Ghanmi

The notion of feedback integrators permits Euclidean integration schemes for dynamical systems evolving on manifolds. Here, a constructive Lyapunov function for the attitude dynamics embedded in an ambient Euclidean space has been proposed.…

Systems and Control · Computer Science 2019-03-26 Tejaswi K. C. , Srikant Sukumar , Ravi Banavar

This paper presents necessary and sufficient characterizations of several notions of input to output stability. Similar Lyapunov characterizations have been found to play a key role in the analysis of the input to state stability property,…

Optimization and Control · Mathematics 2007-05-23 Eduardo D. Sontag , Y. Wang

We consider nonautonomous cyclic systems of delay differential equations with variable delay. Under suitable feedback assumptions, we define an (integer valued) Lyapunov functional related to the number of sign changes of the coordinate…

Dynamical Systems · Mathematics 2025-10-10 István Balázs , Ábel Garab

Understanding learning as a dynamic process is challenging due to the interaction of multiple factors, including cognitive load, internal state change, and subjective evaluation. Existing approaches often address these elements in…

Computers and Society · Computer Science 2026-01-08 Miyuki T. Nakata

This paper tackles state feedback control of switched linear systems under arbitrary switching. We propose a data-driven control framework that allows to compute a stabilizing state feedback using only a finite set of observations of…

Optimization and Control · Mathematics 2022-05-05 Zheming Wang , Guillaume O. Berger , Raphaël M. Jungers

Rapid state control of quantum systems is significant in reducing the influence of relaxation or decoherence caused by the environment and enhancing the capability in dealing with uncertainties in the model and control process. Bang-bang…

Quantum Physics · Physics 2017-06-07 Sen Kuang , Daoyi Dong , Ian R. Petersen

This paper proposes a structural and dynamical framework for modeling cognitive processes within a cybernetic perspective. Cognitive states are represented as elements of a state space evolving through an iterative update rule of the form…

Artificial Intelligence · Computer Science 2026-05-26 Carlo Cattani , Dioneia Motta Monte-Serrat

Lyapunov functions play a vital role in the context of control theory for nonlinear dynamical systems. Besides its classical use for stability analysis, Lyapunov functions also arise in iterative schemes for computing optimal feedback laws…

Optimization and Control · Mathematics 2023-11-03 Tobias Breiten , Bernhard Höveler

This paper presents a counterexample-guided iterative algorithm to compute convex, piecewise linear (polyhedral) Lyapunov functions for uncertain continuous-time linear hybrid systems. Polyhedral Lyapunov functions provide an alternative to…

Optimization and Control · Mathematics 2022-06-23 Guillaume O. Berger , Sriram Sankaranarayanan

Imitation learning is a paradigm to address complex motion planning problems by learning a policy to imitate an expert's behavior. However, relying solely on the expert's data might lead to unsafe actions when the robot deviates from the…

Robotics · Computer Science 2024-11-06 Amin Abyaneh , Hsiu-Chin Lin

We study the dynamical behaviors of this improved memristive neuron model by changing external harmonic current and the magnetic gain parameters. The model shows rich dynamics including periodic and chaotic spiking and bursting, and…

Adaptation and Self-Organizing Systems · Physics 2020-03-03 Marius E. Yamakou