Output feedback tracking control for nonlinear time-delay systems with tracking errors and input constraints

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• 作者：Changchun Hua^a ; ^{cch@ysu.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Guopin Liu^aAuthor Vitae ; Liuliu Zhang^aAuthor Vitae ; Xinping Guan^bAuthor Vitae
• 关键词：Tracking control ; Time-delay systems ; Input constraint ; Error constraint ; RBF neural network
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：15 January 2016
• 年：2016
• 卷：173
• 期：part_P3
• 页码：751-758
• 全文大小：838 K

文摘

The adaptive tracking control problem is considered for a class of nonlinear time-delay systems in the presence of input and tracking error constraint. A reduced-order observer is designed to estimate the unmeasured state variables at first. Then, a constraint variable is utilized to ensure that the tracking error is within the prescribed boundaries. An auxiliary state is introduced to deal with the input saturation constraint. With the time-delay functions unavailable, we employ adaptive RBF neural network systems to approximate unknown functions. It is proved that the resulting closed-loop system is stable in the sense of semiglobal uniformly ultimately boundedness. The simulations are performed and the results demonstrate the effectiveness of the proposed approach.