Event-based adaptive fuzzy control for stochastic nonlinear systems with prescribed performance

Yu Xia, Ke Xiao and Zhibo Geng

Chaos, Solitons & Fractals, 2024, vol. 180, issue C

Abstract: This paper presents an event-based prescribed adaptive fuzzy control scheme for stochastic nonlinear systems. Unlike most existing prescribed performance control schemes, the proposed scheme introduces two tangential envelope functions, one barrier function, and a time-varying scaling transformation. This scheme eliminates the initial boundary constraints on the tracking error and ensures convergence within autonomous asymmetric boundaries in a prescribed time frame. Furthermore, a new event-triggered mechanism is introduced to alleviate the conservative inequality limitations on the trigger parameter design. Additionally, the control scheme integrates a single-parameter-based fuzzy approximator and a command-filtered backstepping design, effectively compensating for approximations and filtering errors while ensuring boundedness in probability for all closed-loop signals. Simulation results confirmed the effectiveness and superiority of the proposed scheme.

Keywords: Adaptive fuzzy control; Event-triggered mechanism; Prescribed performance; Command-filtered backstepping design; Stochastic nonlinear system (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:180:y:2024:i:c:s0960077924000523

DOI: 10.1016/j.chaos.2024.114501

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