Command Filter-Based Finite-Time Adaptive Fuzzy Control for Uncertain Nonlinear Systems With Prescribed Performance

Sun, Wei; Wu, Yuqiang; Sun, Zhigang

doi:10.1109/tfuzz.2020.2967295

Cited by 185 publications

(54 citation statements)

References 50 publications

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“…If the dimension of the systems is high, it will lead to the explosion of complexity and over parameterization problem. In recent literature, the command filtered technique has been proved one of the most effective approaches to address this problem 17‐23 . In particular, in Reference 19, based on fuzzy logic systems and command filtered technology, an adaptive fuzzy tracking control issue was studied for nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, in Reference 19, based on fuzzy logic systems and command filtered technology, an adaptive fuzzy tracking control issue was studied for nonlinear systems. A command filtered‐based finite‐time adaptive fuzzy tracking control problem was investigated in Reference 20 for uncertain nonlinear systems with prescribed performance. The issue of finite‐time control of nonlinear systems was further discussed in References 21,22.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Based on backstepping design method and command filtered technology, an adaptive control scheme was proposed for nonlinear systems in References 18‐23. The designed controller can avoid the problem of explosive complexity caused by repeated derivation of virtual control signals in Reference 18‐23. The systems considered are all nonlinear systems in References 18‐23, which motives us to extend command filtered technology to nonlinear time‐delay systems.…”

Section: Introductionmentioning

confidence: 99%

“…The designed controller can avoid the problem of explosive complexity caused by repeated derivation of virtual control signals in Reference 18‐23. The systems considered are all nonlinear systems in References 18‐23, which motives us to extend command filtered technology to nonlinear time‐delay systems. On the other hand, with the development of network control, it is one of the hot topics to save communication resources and reduce computing burden.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Command filter‐based event‐triggered adaptive neural network control for uncertain nonlinear time‐delay systems

Bao-min

Xia

Sun

et al. 2020

Intl J Robust & Nonlinear

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In this article, the problem of command filter-based adaptive event-triggered neural network control is considered for a class of uncertain nonlinear systems with time delay. Lyapunov-Krasovskii functionals and command filtered technology are utilized to address the problem of unknown time-varying delays and explosion of complexity, respectively. Furthermore, by fusing the event-triggered mechanism, an adaptive tracking controller is designed. The proposed controller not only ensures that the system output eventually follows the desired reference signal in the sufficiently small neighborhood of zero but also reduces the communication resources from the controller to the actuator. Finally, the effectiveness of the proposed control method is verified by a simulation example.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Command filter‐based event‐triggered adaptive neural network control for uncertain nonlinear time‐delay systems

Bao-min

Xia

Sun

et al. 2020

Intl J Robust & Nonlinear

Self Cite

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Decentralized optimal tracking control for large‐scale nonlinear systems with tracking error constraints

Wang

Yang

et al. 2021

Adaptive Control & Signal

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Summary In this article, a decentralized optimal tracking control strategy is proposed for a class of nonlinear systems with tracking error constraints by utilizing adaptive dynamic programming (ADP). It should be noted that ADP technology cannot be directly used to solve decentralized optimal tracking problem of large‐scale interconnected nonlinear system with nonzero equilibrium points, since that an infinite domain performance index function may result in an unsolvable solution. In addition, by introducing a smooth function, the constrained tracking error is transformed into an unconstrained one. Then, the error dynamics and a new infinite domain performance index function are designed, such that ADP technology can be used. Following the designed performance index function, the tracking error can be ensured within a small neighborhood of zero. Finally, the feasibility and the effectiveness of the proposed decentralized optimal control scheme are verified through two simulation examples.

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Command filter‐based adaptive neural event‐triggered control of MIMO pure‐feedback systems with full‐state time‐varying constraints

Zhu

Huang

Ding

et al. 2022

Adaptive Control & Signal

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Summary This article is concerned with the issue of adaptive event‐triggered control for a class of pure‐feedback multi‐input multi‐output (MIMO) nonlinear systems with full‐state time‐varying constraints. By using the hyperbolic tangent as nonlinear mapping technique, the uncertain constrained MIMO non‐affine system is changed into a novel unconstrained MIMO system. Dynamic surface control (DSC) strategy is used to solve the issue of “explosion of complexity.” Command filter is adopted to overcome the insufficient of the DSC method by the error compensation mechanism. Adaptive event‐triggered control scheme is developed for the transformed non‐affine system based on relative threshold mechanism. Radial basis function neural networks are utilized to approximate the unknown nonlinear functions. All the signals in the controlled system are proved to be semi‐globally uniformly ultimately bounded by adding to compensation signals into the whole Lyapunov function. Two simulation examples demonstrate the capability of the proposed control strategy.

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Command Filter-Based Finite-Time Adaptive Fuzzy Control for Uncertain Nonlinear Systems With Prescribed Performance

Cited by 185 publications

References 50 publications

Command filter‐based event‐triggered adaptive neural network control for uncertain nonlinear time‐delay systems

Command filter‐based event‐triggered adaptive neural network control for uncertain nonlinear time‐delay systems

Decentralized optimal tracking control for large‐scale nonlinear systems with tracking error constraints

Command filter‐based adaptive neural event‐triggered control of MIMO pure‐feedback systems with full‐state time‐varying constraints

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