摘要
针对一类不确定状态时滞非线性系统 ,提出了一种形式简单的迭代学习控制算法 ,从理论上给出了算法收敛的充分条件 ,进一步分析了不确定状态时滞、系统采样频率与跟踪性能之间的关系。该学习算法无需精确已知系统的状态时滞 ,而只要估计状态时滞的界 ,因而具有算法简单、计算量小、易于实现等特点。仿真结果表明了该算法的实用性和有效性。
An iterative learning control (ILC) algorithm is proposed for a class of nonlinear systems with uncertain state delay. Convergence conditions are theoretically established. Further analysis is made, which shows the relation of the delay in uncertain states and the sampling frequency with the iterative learning control convergence property. The algorithm only needs estimation bounds of state delay, so it is very simple and easy to implementation. Simulation results demonstrate the effectiveness of the proposed algorithm.\;
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2002年第11期34-36,63,共4页
Systems Engineering and Electronics
基金
江苏省高校自然科学研究指导性计划项目资助课题 (0 1KJD12 0 0 0 1)
