Fuzzy Neural Networks and GA Based Predictive Control for Active Power Filter

A fuzzy neural network and GA based predictive control for active power filter is presented in this paper. In the strategy, fuzzy neural network is employed to predict future harmonic compensating current, in order to make the predictive model compact and accurate, a genetic algorithm with an efficient search strategy is developed to optimize model parameters. Based on the model output, branch-and-bound optimization method is adopted, which generates proper gating patterns of the inverter switches to maintain tracking of reference current without time delay. The predictive algorithm is used in internal model control scheme to compensate for process disturbances, measurement noise and modeling errors. Simulation results show fuzzy neural network and GA based predictive controller gives better harmonic compensation performance than digital adaptive controller.