Finite-time prescribed performance tracking control for nonlinear time-delay systems with state constraints and actuator hysteresis.

Lu, Kexin; Wang, Huanqing; Zheng, Fu; Bai, Wen

Lu, Kexin; Wang, Huanqing; Zheng, Fu; Bai, Wen.

Afiliación

Lu K; The School of Mathematical Sciences, Bohai University, Jinzhou 121000, China. Electronic address: lukexin1103@163.com.
Wang H; The School of Mathematical Sciences, Bohai University, Jinzhou 121000, China. Electronic address: ndwhq@163.com.
Zheng F; The School of Science, Hainan University, Haikou 570100, China. Electronic address: 996040@hainanu.edu.cn.
Bai W; The School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China. Electronic address: wenbai0828@126.com.

ISA Trans ; 153: 295-305, 2024 Oct.

Article en En | MEDLINE | ID: mdl-39117473

ABSTRACT

ABSTRACT

In this paper, the problem of adaptive neural network prescribed performance tracking control for a class of non-strict feedback time-delay systems constrained by full-state is studied. Radial basis function (RBF) neural networks (NNs) are integrated into the backstepping medium to deal with the uncertain functions and the barrier Lyapunov function (BLF) technique ensures that the state of the system does not exceed its limits. Subsequently, integrated with the Lyapunov-Krasovskii functional, the proposed control scheme makes the tracking errors converge to the preset region while the state constraint is not violated. Finally, the effectiveness of the scheme is supported by two simulation experiments.

Palabras clave

Actuator hysteresis; Barrier Lyapunov function; Prescribed performance control; Time-delay systems

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: ISA Trans Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos

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