Forecast iterative learning control with forgetting factor and its application in valve-controlled asymmetric cylinder

Valve-controlled asymmetric cylinder belongs to typical nonlinear and time-varying system at elastic load, in order to eliminate oscillation result from traditional PD-type iterative learning control, a kind of forecast iterative learning control with a forgetting factor is designed. The system mathematical model is built, and the performance characteristics of valve-controlled asymmetric cylinder system are analyzed. The fundamental of iterative learning control is introduced, the problems of traditional PD-type algorithm are analyzed; a forgetting factor is added in the iterative learning control to inhibit the oscillation, the control effect by different forgetting factor value is analyzed by simulating, a part of forecast system given is increased to improve the system accuracy, because forgetting factor lower the system performance. Both simulations and experiments show that, in the valve-controlled asymmetric cylinder system, using forecast iterative learning control with a forgetting factor will overcome oscillation well with a forgetting factor, and can improve accuracy by forecast iterative.