Enhancing model estimation accuracy and convergence rate in hysteresis modeling of MFC actuators using modified differential evolution algorithm

This paper presents a study on improving the estimation accuracy and convergence rate of hysteresis modeling MFC actuators using mutation enhanced differential evolution (MEDE) algorithm, modified version algorithm. The proposed MEDE algorithm uses three strategies, i.e., best, rand, pbest. To model secondary path smart flexible beam with actuators, Hammerstein that combines an asymmetric Bouc-Wen ARX connected in series is proposed. fitness function values are compared evolutionary algorithms.