PARAMETER IDENTIFICATION OF HYSTERETIC MODEL FOR GINAT MAGNETOSTRICTIVE ACTUATOR USING HYBRID GENETIC ALGORITHM
Wenmei Huang · Proceedings of the CSEE · 2004
Aiming at the weak capacity of climbing hill of genetic algorithm, a hybrid intelligent algorithm is established by setting the trust region algorithm in the genetic algorithm. In the proposed hybrid genetic algorithm, the trust region algorithm is taken as a genetic operator which parallels to the selection, crossover and mutation operators. The hybrid algorithm is paid attention to both the advantages of the trust region algorithm and the genetic algorithm. It not only has a rather high convergence speed, but also can locate the best solution with a rather large probability. This paper applies the hybrid genetic algorithm to identify parameters of dynamic model with hysteretic nonlinearity for giant magnetostrictive actuator. The simulation and experimental results show that the hybrid algorithm can efficiently identify nonlinear parameters of nonlinear systems even with system noise.