Adaptive neural network tracking control for a class of switched strict-feedback nonlinear systems with input delay

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• 作者：Ben Niu ; ^{niubenbhu@gmail.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Lu Li ^{lilu00055@163.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Switched nonlinear system ; Adaptive control ; Neural network ; Input delay
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：15 January 2016
• 年：2016
• 卷：173
• 期：part_P3
• 页码：2121-2128
• 全文大小：597 K

文摘

In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach.