Fuzzy model predictive control for active power filter

A fuzzy model predictive control strategy for active power filter is presented in this paper. In the strategy, T-S fuzzy model is employed to predict future harmonic compensating current. The fuzzy model is derived from input-output data by means of product-space fuzzy clustering. In order to make the fuzzy model compact and accurate, similarity driven rule base simplification is applied to detect and merge compatible fuzzy sets in the model and a new validity measure is proposed to determine appropriate number of the clusters. 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 fuzzy model 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 the fuzzy model based predictive controller is effective and feasible.

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