Discrete-time Adaptive Iterative Learning from Different Tracking Tasks with Variable Initial Conditions

作     者：Chi Ronghu 1,Hou Zhongsheng 2,Sui Shulin 1 1.Institute of Autonomous Navigation and Intelligent Control,School of Automation and Electronics Engineering,Qingdao University of Science & Technology,Qingdao 266042,P.R.China2.School of Electronics and Information Engineering,Beijing Jiaotong University,Beijing 100044,P.R.China 

会议名称：《第二十六届中国控制会议》

会议日期：2007年

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

基　　金：supported by National Nature Science Foundation under Grant 60474038 Doctoral Found of Qingdao University of Science & Technology 

关 键 词：Iterative learning control Adaptive control Time-varying parameters Non-identical initial condition Non-identical trajectory 

摘      要：A new discrete-time adaptive iterative learning control（AILC）approach is developed to deal with systems in pres-ence of time-varying parametric *** using the analogy between the discrete time axis and the iterative learning axis,the new adaptive ILC can incorporate a Projection algorithm,hence the learning gain can be tuned iteratively along the learning axis and pointwisely along the time *** major advantage of the new AILC is that it can relax the identical con-ditions on the initial state and reference trajectory,in the sequel achieves an almost perfect tracking performance.