Neural network based predictive control for active power filter

A neural network based predictive control strategy for active power filter is presented in this paper. In the strategy, RBF neural network is employed to predict future harmonic compensating current. In order to make the predictive mode! much simpler and tighter, an adaptive learning algorithm for RBF network is proposed. Based on the model output, genetic algorithm is introduced to optimize objective function, which generates proper value of control vector. The neural network based predictive algorithm is used in internal model control scheme to compensate for process disturbances, measurement noise and modeling errors. Simulation test under various conditions is implemented. The results show the neural network based predictive control is more effective and feasible than PI control or digit adaptive control.