Adaptive neural network control for nonlinear non-strict feedback time-delay systems

IF 3.2 Q2 AUTOMATION & CONTROL SYSTEMS
Yuanyuan Xu, Bing Chen
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引用次数: 4

Abstract

This paper focuses on adaptive neural control for a class of non-strict feedback nonlinear systems with state delays and input delay. By combining integral transformation with adaptive neural control approach, a backstepping-based adaptive neural control scheme is proposed. The suggested control schemes guarantees that the tracking error converges to a small neighbourhood of the origin, meanwhile, all the closed-loop signals remain bounded. Simulation examples are used to verify the effectiveness of the proposed method.
非线性非严格反馈时滞系统的自适应神经网络控制
本文研究了一类具有状态时滞和输入时滞的非严格反馈非线性系统的自适应神经控制。将积分变换与自适应神经控制方法相结合,提出了一种基于反推的自适应神经控制方案。所提出的控制方案保证跟踪误差收敛到原点的一个小邻域,同时所有闭环信号保持有界。通过仿真实例验证了该方法的有效性。
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来源期刊
Systems Science & Control Engineering
Systems Science & Control Engineering AUTOMATION & CONTROL SYSTEMS-
CiteScore
9.50
自引率
2.40%
发文量
70
审稿时长
29 weeks
期刊介绍: Systems Science & Control Engineering is a world-leading fully open access journal covering all areas of theoretical and applied systems science and control engineering. The journal encourages the submission of original articles, reviews and short communications in areas including, but not limited to: · artificial intelligence · complex systems · complex networks · control theory · control applications · cybernetics · dynamical systems theory · operations research · systems biology · systems dynamics · systems ecology · systems engineering · systems psychology · systems theory
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