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  • 标题:Backstepping Iterative Learning Control for Wiener System
  • 本地全文:下载
  • 作者:Lun Zhai ; Guohui Tian ; Yan Li
  • 期刊名称:International Journal of Hybrid Information Technology
  • 印刷版ISSN:1738-9968
  • 出版年度:2016
  • 卷号:9
  • 期号:2
  • 页码:427-438
  • DOI:10.14257/ijhit.2016.9.2.38
  • 出版社:SERSC
  • 摘要:In this paper, the iterative learning control (ILC) scheme combined with the backstepping controller is applied to the Wiener system, which is a typical nonlinear and non-Lipschitz one. The ILC scheme as a feed forward control can improve the convergence speed, and the perfect tracking can be achieved as the system is repeatable. The backstepping control is a feedback control which improves the robustness of the control system, especially for the existence of non-repeatable noises. The backstepping part also guarantees the asymptotic stability, which further improves the convergence speed. The design of backstepping controller is based on the error information in the current control process, and the Lyapunov method. The convergence condition is achieved and the convergence speed is analyzed as well. It can be seen that the combination of ILC scheme and backstepping method can improve the system performance to a large extant. Numerical simulations validate the above conclusions.
  • 关键词:ILC; backstepping; Wiener system; convergence condition; convergence ; speed; system performance
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