摘要
本文首先回顾了迭代学习控制中初始状态漂移问题和单调收敛性分析的研究技术.其次,综述了高阶迭代学习控制机制及其收敛速度比较和有效性.再次,评述了重复运行大系统和变幅值大工业过程的迭代学习控制机理.最后,展望了长期学习控制的研究趋势等.
This paper firstly makes a retrospective review of some iterative learning control techniques and results regarding to the initial state shift issue and the monotone convergence analysis.Secondly,the paper presents a review of the higher-order iterative learning control scheme including its convergence speed comparison and effectiveness.Then,the paper exhibits a review of iterative learning control mechanism for large-scale systems including repetitive systems and magnitude-varying industrial processes.Lastly,the paper gives a comment on prospective long-term learning control for the future.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2012年第8期966-973,共8页
Control Theory & Applications
基金
supported by the National Natural Science Foundation of China(No.F030114-60974140)
the Funding of Intelligent Robot Research Center,Soongsil University,Korea
关键词
迭代学习控制
收敛性分析
初始状态漂移
高阶学习律
大系统
长期学习控制
iterative learning control
convergence analysis
initial state shift
higher-order learning law
large-scale systems
long-term learning control
