这份报纸论述为有多重状态的连续时间的系统的问题推迟的反复的学习控制(ILC ) 的稳定性分析,特别当系统参数服从于 polytopic 类型无常时。用二维(2-D ) ILC 的分析途径,连续分离的 Roesser 的类型线性系统被采用与一个膨胀操作员的发展描述时间延期系统(TDS ) 的全部学习动力学。基于如此的 Roesser 系统, 2-D 系统理论首先被用来为 ILC,然后 robustH 控制理论的 asymptotic 稳定性开发一个必要、足够的条件被联合为 ILC 的 monotonic 集中以线性矩阵不平等(LMI ) 提供一个足够的条件。学习获得能由解决 LMI 是坚定的,这被显示出,它保证控制输入错误作为重复的一个函数 monotonically 收敛到零。一个柔韧的 asymptotically 稳定的 ILC 计划能要用体力地变得的模拟结果表演由增加学习满足一套 LMI 的获得的 P 类型 monotonically 会聚,它能也极大地改进集中率。
This paper presents a stability analysis of the iterative learning control (ILC) problem for continuous-time systems with multiple state delays,especially when system parameters are subject to polytopic-type uncertainties.Using the two-dimensional (2-D) analysis approach to ILC,the continuous-discrete Roesser s type linear systems are employed to describe the entire learning dynamics of time-delay systems (TDS) with the development of an expanding operator.Based on such Roesser systems,the 2-D system theory is first used to develop a necessary and sufficient condition for the asymptotic stability of ILC,and then the robust H∞ control theory is combined to provide a sufficient condition in terms of linear matrix inequalities (LMIs) for the monotonic convergence of ILC.It is shown that learning gains can be determined by solving LMIs,which ensure the control input error converges monotonically to zero as a function of iteration.Simulation results show that a robust asymptotically stable ILC scheme can become robustly monotonically convergent by adding the P-type learning gains that satisfy a set of LMIs,which can also improve the convergence rate greatly.