Finite-Time Adaptive Fuzzy Command Filtered Backstepping Control for a Class of Nonlinear Systems

Wang, Huanqing; Kang, Shijia; Feng, Zhiguang

doi:10.1007/s40815-019-00749-0

Cited by 44 publications

(13 citation statements)

References 55 publications

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“…However, in many practical applications, the system need to do a fast transient response. Therefore, in order to complete the high precision requirements of the system performance, the finite‐time control has been attracted extensive attention 32‐38 . For example, the stabilization of a class of uncertain nonlinear systems with the powers of positive odd rational numbers is investigated by adaptive finite‐time control in the works of Fu et al 37 …”

Section: Introductionmentioning

confidence: 99%

Finite‐time adaptive fault‐tolerant tracking control for nonlinear switched systems with dynamic uncertainties

Cui

Xiang

2021

Intl J Robust & Nonlinear

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In this paper, a finite‐time adaptive fault‐tolerant control (FTC) scheme is researched for a class of nonlinear systems with unmodeled dynamics, where the dynamic system is switched. Due to the complexity of the system and switching characteristics, it is not easy to solve the tracking problem in a finite time adopting existing approaches. In this study, a new FTC method is presented. This is completed by using the backstepping technology, common Lyapunov function method, and radial basis function (RBF) neural networks (NNs) which are utilized to estimate unknown functions. It is shown that all signals in the closed‐loop system are semi‐global bounded under arbitrary switching, and the tracking error converges to a small region around the origin in a finite time. An effective simulation example is given to prove the practicability of the designed scheme in the end.

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Section: Introductionmentioning

confidence: 99%

Finite‐time adaptive fault‐tolerant tracking control for nonlinear switched systems with dynamic uncertainties

Cui

Xiang

2021

Intl J Robust & Nonlinear

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“…For the above cases, it is essential to find a good control method to highlight the advantages of the PMSMs drive systems. In the last decade, relevant scholars have put forward various control methods, such as backstepping control [4]- [8], sliding mode control [9]- [12], adaptive control [13]- [16], command filtered control (CFC) [17]- [19] and so on.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fuzzy Observer-Based Command Filtered Discrete-Time Control for PMSMs With Input Constraint

Liu

Lei

et al. 2021

IEEE Access

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This paper proposes an adaptive fuzzy observer-based command filtered discrete-time control method for permanent magnet synchronous motors (PMSMs) with input constraint. First, the rotor angular velocity is estimated by using an adaptive fuzzy observer, and the unknown nonlinear function is approximated by using fuzzy logic systems (FLSs) in the PMSMs drive systems. Then, compared with the traditional backstepping method, command filtered backstepping method is developed to solve the "complexity of computation" problem. It is shown that all signals of the closed-loop system are semiglobally uniformly ultimately bounded. Finally, the results of the simulation and experiment demonstrate that the new design method can fully consider the influence of input constraint and load disturbance, and improve the tracking performance for PMSMs drive systems.

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“…Besides, the improved backstepping design without virtual control laws was proposed by Bu et al 9,10 Furthermore, the complexity explosion problem can be eliminated well by the command filter. 11–13 Recently, a command filter-based adaptive fuzzy controller has been proposed for a class of nonlinear systems with uncertain disturbance. 14 Feng et al 15 proposed a novel adaptive finite-time backstepping tracking control with command filter for a class of uncertain nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Command filtered adaptive neural tracking control of uncertain nonlinear time-delay systems with asymmetric time-varying full state constraints and actuator saturation

Fang

2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article investigates the command filtered adaptive neural tracking control for uncertain nonlinear time-delay systems subject to asymmetric time-varying full state constraints and actuator saturation. To stabilize such a class of systems, the radial basis function neural networks and the backstepping technique are used to structure an adaptive controller. The command filter is utilized to overcome the complexity explosion problem in backstepping. By employing the Lyapunov–Krasovskii functionals, the effect of time-delay is eliminated. The asymmetric time-varying barrier Lyapunov functions are designed to ensure full state constraint satisfaction. Moreover, the hyperbolic tangent function and an instrumental variable are introduced to deal with actuator saturation. All signals in the closed-loop system are proved to be bounded and the tracking error converges to a small neighborhood of the origin. Finally, two examples are provided to illustrate the effectiveness of the proposed method.

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Finite-Time Adaptive Fuzzy Command Filtered Backstepping Control for a Class of Nonlinear Systems

Cited by 44 publications

References 55 publications

Finite‐time adaptive fault‐tolerant tracking control for nonlinear switched systems with dynamic uncertainties

Finite‐time adaptive fault‐tolerant tracking control for nonlinear switched systems with dynamic uncertainties

Adaptive Fuzzy Observer-Based Command Filtered Discrete-Time Control for PMSMs With Input Constraint

Command filtered adaptive neural tracking control of uncertain nonlinear time-delay systems with asymmetric time-varying full state constraints and actuator saturation

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