Improvement And Application Of Iterative Learning Control Algorithm

Iterative learning control is a control method that uses the input information and thetracking errors of last time to modify the current control input, with the respect of the outputof controller can completely or gradual tracking the desired trajectory through a certainnumber of repeat. Because of the simple and convenient to use, this method has been noticedby lots of researchers. In this paper, the improved iterative learning algorithm is considered,and applied to the typical systems and normal linear systems. The main contents are asfollows:In the first part, a hybrid PID controller is proposed which is combined the normal PIDcontroller based on LQR(linear quadratic regulator) with the Iterative Learning Control.Tracking control problems of elevation and travel angles are investigated for3-DOF(threedegree of freedom) helicopter in this paper. And through the MATLAB simulations aboutthese two aspects, we can see that this method improves the tracking accuracy.In the second part, we combined the fuzzy controller with normal iterative controller toadjust learning gain. The one input of the first fuzzy controller is the input of the last iterative,and the output is the change of learning gain. Based on conventional P-type iterative learningcontroller, we got P-type fuzzy iterative learning controller. After that, we used MATLAB tosimulate this new kind of controller, the results show that the new kind of fuzzy iterativelearning controller has better performance than the traditional one.In the third part, we developed a new model of P-type iterative learning controller onthe basic of traditional one. We used the function of logarithm in the gain of controller, andwe proved the convergence of this method in the continuous and discrete systems respectively.We did the simulations in the regular two order linear time-invariant system and speedgoverning control system for switched reluctance motor, the results show that the proposedapproach has faster speed and higher precision than the traditional one.