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Fuzzy Gain PD Type Iterative Learning Control Algorithm and Its Application

JIANG Sizhong,ZHU Fanglai,WANG Xinkai,WANG Gaiyun(School of Computer & Control,Guilin University of Electronic Technology,Guilin 541004,China)  
The common Proportional Integration Differential(PID) type Iterative Learning Control(ILC) algorithm has a lower convergence rate since its gain matrix is constant.To improve the convergence rate,the fuzzy control law is introduced in ILC and a kind of fuzzy gain PD type iterative learning control algorithm is developed.The algorithm can regulate the gain matrices by adjusting the factors according to system error information.The adjustment method is: 1) At the initial stage of control,enhancing the system error gain matrix while keeping the error differential gain matrix invariant,so the errors can be eliminated;2) When control tends stable,enhancing the error differential gain matrix while keeping the system error gain matrix invariant,thus to reduce the overshoot.The simulation results for a single arm robotic model show that the method is feasible.
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