Optimization-based fuzzy iterative learning control

Summary from only given. In this paper a new approach to fuzzy iterative learning control is presented. The method keeps the advantage of ILC while create appropriate updating law by using fuzzy TSK system that can deal with nonlinearities and uncertainties. Finally coefficients of fuzzy system and learning rate of ILC are calculated by using optimization algorithms such as steepest descent and genetic algorithm. The overall developed fuzzy iterative learning controller is called FILC. Finally the controller is applied to electro hydraulic servo actuator as a highly nonlinear and uncertain system and simulation results show prior advantages of the method.