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  • 标题:Generalized Norm Optimal Iterative Learning Control: Constraint Handling
  • 本地全文:下载
  • 作者:Yiyang Chen ; Bing Chu ; Christopher T. Freeman
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2017
  • 卷号:50
  • 期号:1
  • 页码:13396-13401
  • DOI:10.1016/j.ifacol.2017.08.2275
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper proposes a novel control methodology to incorporate constraint handling within generalized iterative learning control (ILC), an overarching methodology which includes intermediate point and sub-interval tracking as special cases. The constrained generalized ILC design objective is first described, and then the design problem is formulated into a successive projection framework. This framework yields a constrained generalized ILC algorithm which embeds system input and output constraints. Convergence analysis of the algorithm is performed and supported by rigorous proofs. The algorithm is verified using a gantry robot experimental platform, whose results reveal its practical efficacy and robustness against plant uncertainty.
  • 关键词:Keywordsiterative learning controlconstraint handling
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