Finite-Time Adaptive Control for a Class of Nonlinear Systems With Nonstrict Feedback Structure
Finite-Time Adaptive Control for a Class of Nonlinear Systems With Nonstrict Feedback Structure
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一类非严格反馈结构非线性系统的有限时间自适应控制
DOI：
10.1109/tcyb.2017.2749511
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发表时间：
2018-10
影响因子：
11.8
通讯作者：
Wang Honghong
中科院分区：
文献类型：
--
作者：
Sun Yumei;Chen Bing;Lin Chong;Wang Honghong
研究非严格反馈非线性系统的有限时间自适应神经跟踪控制。首先提出了半全局有限时间实用稳定性判据。相应的，利用该准则给出了有限时间自适应神经控制策略。与已有的自适应神经/模糊控制结果不同，本文提出的自适应神经控制器保证跟踪误差在有限时间内收敛到原点周围足够小的域内，其他闭环信号是有界的。最后，通过两个算例验证了所得结果的有效性。
This paper focuses on finite-time adaptive neural tracking control for nonlinear systems in nonstrict feedback form. A semiglobal finite-time practical stability criterion is first proposed. Correspondingly, the finite-time adaptive neural control strategy is given by using this criterion. Unlike the existing results on adaptive neural/fuzzy control, the proposed adaptive neural controller guarantees that the tracking error converges to a sufficiently small domain around the origin in finite time, and other closed-loop signals are bounded. At last, two examples are used to test the validity of our results.