Neural Observer and Adaptive Neural Control Design for a Class of Nonlinear Systems
Neural Observer and Adaptive Neural Control Design for a Class of Nonlinear Systems
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一类非线性系统的神经观测器与自适应神经控制设计
DOI：
10.1109/tnnls.2017.2760903
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发表时间：
2018
影响因子：
10.4
通讯作者：
Lin Chong
中科院分区：
文献类型：
--
作者：
Chen Bing;Zhang Huaguang;Liu Xiaoping;Lin Chong
研究了非线性非严格反馈系统的自适应神经元跟踪控制问题。状态变量是不可测的，只有系统输出是可用的。构造了一个神经网络观测器来估计这些未知的系统状态变量。基于反推方法，提出了一种自适应神经元跟踪控制方案。结果表明，所设计的控制器保证系统输出很好地跟踪期望的参考信号，同时，其他闭环信号保持有界。最后，通过两个仿真算例对结果进行了验证.
This paper addresses the problem of adaptive neural tracking control for nonlinear nonstrict-feedback systems. The state variables are immeasurable and only the system output is available. A neural observer is constructed to estimate these unknown system state variables. An observer-based adaptive neural tracking control scheme is developed via backstepping approach. It is shown that the designed controller guarantees that the system output well follows the desired reference signal, and meanwhile, other closed-loop signals remain bounded. Finally, two simulation examples are used to test our results.