Support Vector Machine based Predictive Control for Active Power Filter

A support vector machine (SVM) based predictive control strategy for active power filter is presented in this paper. In the strategy, SVM is employed to model and predict future harmonic compensating current, it has the advantages of nonexistence of local minima solutions, automatic choice of model complexity and good generalization performance. Based on the model output, branch-and-bound optimization method is adopted to produce proper value of control vector, this value is adequately modulated by means of a space vector PWM modulator which generate proper gating patterns of the inverter switches to maintain tracking of reference current. The SVM based predictive algorithm is used in internal model control scheme to compensate for process disturbances, measurement noise and modeling errors. The proposed control is applied to compensate the harmonic produced by the variable non-linear load, simulation results show SVM based predictive controller is effective.