Adaptive Output Feedback Fuzzy Fault-Tolerant Control for Nonlinear Full-State-Constrained Switched Systems

Tang, Li; Yang, Meiying; Liu, Yanjun; Tong, Shaocheng

doi:10.1109/tcyb.2021.3116950

Cited by 11 publications

(1 citation statement)

References 53 publications

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“…In fact, the problem of state constraints has been solved well by constructing barrier Lyapunov functions (BLFs), and different types of BLFs have been proposed, including tangent‐BLFs, 33 integral‐BLFs 34 and logarithmic‐BLFs 35,36 . Furthermore, by combining BLFs and FLSs or NNs, many adaptive tracking control methods have been researched for different nonlinear systems with full‐state constraints, such as nonlinear systems, 37‐39 switched nonlinear systems, 40 nonlinear time‐delay systems, 41 high‐order nonlinear time‐delay systems 42 and stochastic nonlinear systems 43 . It is worth pointing out that authors in Reference 44 and 45 investigated the tracking control issues of stochastic nonlinear systems with full‐state constraints, and proposed a novel MTN‐based adaptive control scheme with the help of the BLFs method.…”

Section: Introductionmentioning

confidence: 99%

Switching threshold‐based event‐triggered adaptive asymptotic tracking control for stochastic nonlinear systems with full‐state constraints

Zhu

Zhai

et al. 2023

Intl J Robust & Nonlinear

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In this article, the problem of event-triggered adaptive asymptotic tracking control (ATC) for stochastic nonlinear systems with unknown control directions (UCDs) and full state constraints is concerned. It must be said that the controller design and system analysis is more complex and difficult since the existence of stochastic disturbances, UCDs and full state constraints simultaneously. By introducing the lower bound of the UCDs into the barrier Lyapunov functions, an event-triggered adaptive MTN ATC scheme is proposed based on the boundary estimation method and a new event-triggered control (ETC) strategy, which can achieve satisfactory asymptotic tracking performance and control performance of the system, while reduce the occupation of network resources. The simulation results not only verify the effectiveness of the proposed control scheme, but also present different tracking performances between three ETC strategies for comparison, further confirming the superiority of the proposed ETC strategy in achieving asymptotic tracking performance.

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