退化高阶抛物型分布参数系统的迭代学习控制
Iterative learning control for degenerating higher order parabolic distributed parameter systems
摘要点击 141  全文点击 186  投稿时间:2018-01-22  修订日期:2018-07-31
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DOI编号  10.7641/CTA.2018.80069
  2019,36(7):1147-1152
中文关键词  迭代学习控制  高阶分布参数系统  退化抛物型方程  P型学习算法
英文关键词  iterative learning control  higher order distributed parameter systems  degenerating parabolic equations  P-type learning algorithm
基金项目  国家自然科学基金项目(61374104, 61773170), 广东省自然科学基金项目(2016A030313505)资助.
学科分类代码  
作者单位E-mail
顾盼盼 华南理工大学 1005131776@qq.com 
田森平 华南理工大学 ausptian@scut.edu.cn 
中文摘要
      研究一类高阶分布参数系统的迭代学习控制问题, 该类系统由退化高阶抛物型偏微分方程构成. 根据系统所满足的性质, 基于P型学习算法构建得到迭代学习控制器. 利用压缩映射原理, 证明该算法能使得系统的输出跟踪误差于L^2空间内沿迭代轴方向收敛于零. 最后, 仿真算例验证了算法的有效性.
英文摘要
      The problem of iterative learning control for a class of higher order distributed parameter systems is studied. Here, the considered distributed parameter systems are composed of degenerating higher order parabolic partial differential equations. According to the characteristics of the systems, iterative learning control laws are proposed for such higher order distributed parameter systems based on P-type learning algorithm. Using the contraction mapping method, it is shown that the algorithm can guarantee the output tracking errors on L^2 space converge to zero along the iteration axis. Finally, an example is constructed to illustrate the effectiveness of the proposed algprithm.