北京交通大学学报2012，Vol.36Issue(2)：70-73,84,5.
不确定时滞系统的PD型迭代学习控制算法
PD-type learning algorithm for uncertain control time-delay systems
摘要
Abstract
In the paper, for a class of NCS with uncertain time delay, a PD-type iterative learning algorithm (ILC) is studied to compensate it. Based on the strict repetition of the initial state, the sufficient conditions which guarantee the uniform convergence of the ILC are given. And the limit output trajectories generated by the action of the ILC are also presented. Then, comparing with the efficiency of the P-type ILC algorithm, it is shown that the PD-type ILC is more effective to compensate the time delay. For the case that the range of the time delay becomes smaller, it can track the output trajectories precisely than the P-type ILC algorithm. Moreover, under the same number of iteration, the PD-type ILC algorithm can track the state trajectories faster than the PD-type ones.关键词
网络时滞/迭代学习控制/严格重复/不确定时滞系统Key words
network time-delay/ iterative learning control algorithm/ strictly repetition of the initial state/ uncertain time-delay control systems分类
信息技术与安全科学引用本文复制引用
张严心,徐健洲..不确定时滞系统的PD型迭代学习控制算法[J].北京交通大学学报,2012,36(2):70-73,84,5.基金项目
国家自然科学基金资助项目(60904014) （60904014）
