Predictive functional control based on differential evolution algorithm and its dynamic performance analysis

Abstract

An optimization method of predictive function control (PFC) parameters that based on modified differential evolution (DE) is provided. Differential evolution is a new evolutionary computation technology and exhibits good performance on optimization. Differential evolution algorithm as a relatively new evolutionary computation technique has a good optimization. Therefore, the modified differential evolution which is proposed to solve the optimization problems. The new algorithm uses initialization and the scale factor and crossover probability to improve PFC control performance in terms of model mismatch and parameters optimization. Simulation results show that the performance of the optimized DE PFC controller is superior to that of the conventional PFC controller.