线性时变系统变初始条件变期望轨迹的迭代学习控制(英文)  

Iterative learning control for linear time-variant continuous systems with iteration-varying initial conditions and reference trajectories

作　　者：戴辉[1,2] 卢益民[2] 

机构地区：[1]海南软件职业技术学院,琼海571400 [2]华中科技大学电子与信息工程系,武汉430074

出　　处：《中国科学院研究生院学报》2011年第3期366-374,共9页Journal of the Graduate School of the Chinese Academy of Sciences

基　　金：Supported by the National Natural Science Foundation of China(60874116);Natural Science Foundation of Hainan province(610227)

摘　　要：对于非严格重复线性时变连续系统,初始迭代条件和参考轨迹在一定带宽范围内都是迭代变化的.提出一种非严格的迭代学习方法来控制跟踪整流.通过该方法所获得的控制器,能保证闭环系统的所有信号是全局有界的,能够使超出初始时间间隔的输出跟踪误差收敛到一个小的残差集内,该残差集大小取决于输入矩阵的估测误差.尤其是当输入矩阵已知的情况下,能够让超出的初始时间间隔输出跟踪误差趋近于零.For non-strictly repetitive linear time-variant continuous systems,both the iterative initial conditions and the reference trajectories are iteration-varying within a bound.We present a kind of iterative learning controller with a rectifying action to the non-strictly repetitive tracking.The proposed controller can make the output tracking error beyond the initial time interval converge to a residual set whose size depends on the estimation error of input matrix.Especially,when the accurate input matrix is known,the output tracking error beyond the initial time interval can approach zero.

关 键 词：线性时变系统 变初始条件 迭代变期望轨迹 迭代学习控制 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]