Dynamic events-based adaptive NN output feedback control of interconnected nonlinear systems under general output constraint.

Meng, Rui; Hua, Changchun; Li, Kuo; Li, Qidong · Neural Netw · 2025

basic_science · Level V

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Abstract

This paper investigates the adaptive NN output feedback tracking control problem for a class of interconnected nonlinear systems. Unlike the existing control algorithms, we propose a dynamic event-triggered output constraint control algorithm.First, a reduced-order dynamic gain K-filter is established to construct the unmeasurable state variables. Second, an asymmetric constraint function with a special time-varying function is proposed, which can handle the case where the initial values of the constraint boundaries are unlimited. Then, a dynamic event-triggered mechanism based on the arctangent function is developed, which avoids the continuous transmission of control signals. With the help of the Lyapunov stability theory, it is rigorously proved that all signals of the closed-loop systems are bounded and the tracking error satisfies the output constraint requirement.Finally, the validity of the proposed algorithm is justified by the use of a numerical simulation.

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