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线性广义系统的迭代学习控制
引用本文:朴凤贤,张庆灵. 线性广义系统的迭代学习控制[J]. 控制与决策, 2007, 22(3): 349-351
作者姓名:朴凤贤  张庆灵
作者单位:东北大学,系统科学研究所,沈阳,110004;沈阳航空工业学院,理学系,沈阳,110034;东北大学,系统科学研究所,沈阳,110004
基金项目:国家自然科学基金项目(60574011);辽宁省普通高校学科带头人基金项目(124210).
摘    要:针对线性时不变广义系统的迭代学习控制问题.利用时间加权范数性质.通过Frobenius范数给出广义系统在D型和PD型闭环学习律作用下系统的实际输出轨迹逐渐逼近理想输出轨迹的充分条件.并指出在D型闭环学习律的基础上加上P型闭环学习律不影响控制系统的收敛性.但可以改变系统的性能.仿真算例说明了该方法的有效性.

关 键 词:广义系统  迭代学习控制  学习律  收敛
文章编号:1001-0920(2007)03-0349-03
收稿时间:2005-12-05
修稿时间:2005-12-052006-02-16

Iterative learning control for linear singular systems
PIAO Feng-xian,ZHANG Qing-ling. Iterative learning control for linear singular systems[J]. Control and Decision, 2007, 22(3): 349-351
Authors:PIAO Feng-xian  ZHANG Qing-ling
Affiliation:1. Institute of Systems Science, Northeastern University, Shenyang 110004, China. 2. Department of Science, Shenyang Institute of Aeronautical Engineering, Shenyang 110034, China
Abstract:The problem of iterative learning control for linear singular systems is investigated. According to the time weighted norm property, a sufficient condition for the D-type and PD-type learning law making closed-loop system converge is derived by the Frobenius norm and the actual output trajectory converges to the desired trajectory under constraint. At the same time, the results show that the P-type closed-loop learning law does not change the convergence of the system with D-type closed-loop learning law, but changes the performance of the system. A numerical example shows the effectiveness of the proposed approach.
Keywords:Singular system   Iterative learning control   Learning law   Convergence
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