HiTL-based adaptive fuzzy tracking control of MASs: A distributed fixed-time strategy

Liu, Yang; Chi, RongHu; Li, HongYi; Wang, LiJie; Lin, Na

doi:10.1007/s11431-022-2319-6

Cited by 36 publications

(2 citation statements)

References 48 publications

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“…Compared with the asymptotic stability, the finite-time control (FTC) can achieve faster convergence speed, higher control accuracy and better robustness, and disturbance resistance. 29,30 Therefore, the FTC has attracted widespread attention in recent years, and many results have been obtained for different nonlinear systems with different assumptions, such as nonlinear uncertain systems, 31,32 MIMO nonlinear systems, 33 fuzzy switched cyber-physical systems, 34 uncertain rigid spacecraft systems, 35 heterogeneous vehicles systems, 36 quantized nonlinearly parameterized systems, 37 multi-agent systems, 38,39 and Markov jump systems. 40 Most interestingly, utilizing the approximation of FLSs or NNs, many adaptive backstepping control approaches have been developed for stochastic nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Adaptive finite‐time control for a class of stochastic nonlinear systems with input saturation constraints: A new approach based on multidimensional Taylor network

Han,

Sun

2024

Intl J Robust & Nonlinear

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This article proposes a novel multidimensional Taylor network (MTN)‐based adaptive finite‐time control approach for stochastic nonlinear systems with input saturation constraints. First, by introducing the hyperbolic tangent function, a piecewise smooth function is proposed to approximate the input saturation constraints, which can solve the problem caused by input saturation. Then, with the aid of MTN approximation theorem, a novel adaptive finite‐time control approach is proposed, which can guarantee that all signals of the closed‐loop system are semi‐globally finite‐time stability in probability (SGFTSP), the system output follows the given reference signal, meanwhile, the tracking error converges to a small neighborhood of the origin in finite‐time. Compared with the existing results, the proposed approach has the characteristics of simple structure and low calculation, which can achieve the satisfactory control performance with a reduced computational burden. In the end, the effectiveness of the proposed approach is validated by Lyapunov stability theory and two simulation experiments.

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Section: Introductionmentioning

confidence: 99%

Adaptive finite‐time control for a class of stochastic nonlinear systems with input saturation constraints: A new approach based on multidimensional Taylor network

Han,

Sun

2024

Intl J Robust & Nonlinear

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“…The cooperative control schemes for multiagent systems (MASs) [1][2][3][4][5][6][7][8][9][10][11][12] have been broadly discussed over the past few years. To achieve the consensus control objective between [20] investigated the asymptotic tracking control issue for nonlinear time-delay systems.…”

Section: Introductionmentioning

confidence: 99%

A Novel Communication Time-Delay Cooperative Control Method with Switching Event-Triggered Strategy

Li,

Cao,

Pan

et al. 2024

J Intell Robot Syst

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A novel communication time-delay classification-based method is designed for nonlinear multiagent systems with the finite-time prescribed performance function. The time-delay phenomenon for communication channels between agents is discussed. Then, an improved time-delay classification method is proposed to broaden the standard of classification mechanism by considering the degree of deviation and relative variation of neighbor agents, rather than classifying the delay time into large time-delay and small time-delay. Based on this, the unified Lyapunov-Krasovskii functional and the finite-time performance function are used to solve the large time-delay phenomenon and ensure that the error is within the preset boundary, respectively. Furthermore, a modified switching event-triggered strategy is put forward to reduce the transmission burden, which considers the impact of tracking error to adjust the threshold condition in real-time. Additionally, all signals of the closed-loop systems are bounded. Eventually, two simulation examples verify the validity of the control strategy.

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Adaptive neural network finite‐time control for fractional‐order nonlinear systems with external disturbance

Shang,

Lin,

et al. 2024

Asian Journal of Control

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This paper is concerned with the finite‐time tracking control problem of fractional‐order nonlinear systems (FONSs) with uncertainty and external disturbance. A novel design scheme of the adaptive neural network finite‐time controller (ANNFTC) is developed by utilizing the theory of finite‐time stability and fractional‐order dynamic surface control (DSC) scheme combined with backstepping method. Radial basis function neural networks (RBF NNs) are employed to estimate the unknown nonlinear function. Furthermore, an auxiliary function is introduced to approximate the unknown upper bounds of the approximation error in RBF NNs and external disturbance. The ANNFTC ensures the finite‐time boundedness of all signals in FONSs and enhances the system output's tracking performance. The effectiveness of the proposed approach is demonstrated through a simulation example, providing empirical evidence to support the theoretical framework presented in this paper.

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HiTL-based adaptive fuzzy tracking control of MASs: A distributed fixed-time strategy

Cited by 36 publications

References 48 publications

Adaptive finite‐time control for a class of stochastic nonlinear systems with input saturation constraints: A new approach based on multidimensional Taylor network

Adaptive finite‐time control for a class of stochastic nonlinear systems with input saturation constraints: A new approach based on multidimensional Taylor network

A Novel Communication Time-Delay Cooperative Control Method with Switching Event-Triggered Strategy

Adaptive neural network finite‐time control for fractional‐order nonlinear systems with external disturbance

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