4.7 Article

Robust Stabilization of Uncertain Switched Nonlinear Systems With Hybrid Saturated Inputs

Journal

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
Volume 53, Issue 8, Pages 5084-5095

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2023.3260265

Keywords

Control systems; Switches; Nonlinear systems; Actuators; Switched systems; Uncertain systems; Optimization; Attraction domain; impulsive control; sampled-data control; saturation; uncertain switched nonlinear system

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In this article, a novel class of mathematical models for uncertain switched nonlinear systems with saturation constraints on control signals is proposed. The robust stability of the system is analyzed using Lyapunov stability theory, polytopic representation approach, matrix inequality, and Schur complement. Design of the hybrid control gains and optimization problems for larger estimation of the attraction domain are also investigated. Simulation results show the feasibility and effectiveness of the proposed methods.
In this article, we propose a novel class of mathematical models of uncertain switched nonlinear systems with saturation constraints on both the sampled-data control signal and the impulsive signal, which can reflect the actuator saturation phenomenon of hybrid control signals more realistically. Based on the Lyapunov stability theory, polytopic representation approach, matrix inequality, and Schur complement, we analyze the robust stability of the considered system, overcoming the relevant difficulties from the parameter uncertainty, the discontinuity produced by impulsive effect and the input constraints on both the sampled-data control signal and the impulsive signal. Moreover, to make it easier to find the suitable control gains, the design of the hybrid control gains is investigated. And, some optimization problems are also established to obtain the larger estimation of the attraction domain. Simulation results for the system consisting of two neural network subsystems are presented to show the feasibility and effectiveness of our robust stabilization methods and the LMI optimization problems.

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