A Newton-type Iterative Learning Algorithm of Output Tracking Control for Uncertain Nonlinear Distributed Parameter Systems

摘要：

　　A new iterative learning algorithm of output tracking control for uncertain nonlinear distributed parameter systems is considered in this paper.The iterative learning control scheme based on Newton-type method is constructed.Sufficient conditions for the convergence of this new algorithm are given.Using Green formula and the operator Taylor expansion method in Banach space,the convergence of the Newton-type iterative learning control algorithm is proved.The significant of this paper is to provide a Newton-type iterative learning control scheme with rapid convergence speed,which is a new method for solving the output tracking problem in distributed parameter systems.

关键词： Iterative learning control Nonlinear distributed parameter systems Newton method Parabolic partial differential equations

作者: KANG Jingli

作者单位: The Fourth Academy,China Aerospace Science and Technology Corporation,Beijing 102308

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 8901-8905

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）