Command-filter-based neural networks predefined time control for switched nonlinear systems with event-triggering mechanism

Yu Yang, Wenshan Bi, Shuai Sui and C.L. Philip Chen

Applied Mathematics and Computation, 2025, vol. 491, issue C

Abstract: The article proposes a dynamic event-triggered adaptive predefined time output feedback control technique for uncertain switching multi-input multi-output (MIMO) nonlinear systems with strict feedback forms. In contrast to previous event-triggered output feedback control, the control technique proposed in this study not only enables the system to reach steady state within a predefined time, but also further saves communication resources. Subsequently, the unpredictable states of the system are modeled using a neural network (NN) state observer. In the framework of backstepping control, an output feedback control strategy based on command filtering is proposed. Finally, the stability for a switched nonlinear system has been demonstrated using predefined time stability theory and average dwell time (ADT). The results concern this semi-global practically predefined time stabilization (SGPPTS) of all signals in the closed-loop system. Simulations and comparisons are utilized to verify the predefined time control characteristics.

Keywords: Command filter; Predefined time stability; Event-triggered control (ETC); Switched nonlinear system; Average dwell time (ADT) (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:491:y:2025:i:c:s0096300324006660

DOI: 10.1016/j.amc.2024.129205

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