线性广义系统的迭代学习控制  

Iterative learning control for linear singular systems

作　　者：朴凤贤[1] 张庆灵[1] 

机构地区：[1]东北大学系统科学研究所

出　　处：《控制与决策》2007年第3期349-351,356,共4页Control and Decision

基　　金：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.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.

关 键 词：广义系统 迭代学习控制 学习律 收敛 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]