摘要
针对迭代学习控制在非最小相位系统上应用效果差的缺点,根据最优化性能指标和非因果的稳定逆理论,提出了一种基于稳定逆的最优开闭环综合迭代学习控制,分析了学习律的收敛性并给出了此种非因果的学习律在实际应用中的运用方式.
In order to deal with the poor tracking effect which occurs when the iterative learning control (ILC) was applied to the non-minimum phase system, an optimal ILC scheme with current feedback was presented for linear non-minimum phase plants based on an optimality criterion and noncausal stable inversion. The convergence of this scheme was analyzed and the utility mode of using the noncausal algorithm was proposed for the practical application.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2003年第6期831-837,共7页
Control Theory & Applications
基金
国家"863"高技术研究发展计划项目(2002AA412010)
国家自然科学基金项目(69874035).
关键词
迭代学习控制
稳定逆
非最小相位系统
学习律
收敛性
iterative learning control
non-minimum phase
noncausal stable inversion
optimality criterion
