Adaptive Genetic Algorithm with Heuristic Weighted Crossover Operator Based Hysteresis Identification and Compensation

A genetic algorithm with adaptive search space (GAASS) and a new crossover operator named heuristic weighted crossover operator (HWCO) are proposed, then applied to identify the hysteresis model parameters of an electromechanical-valve actuator installed on a pneumatic system. According to the normalized fitness distance in each generation, the proposed GAASS method consistently identifies the best search domains in the parameter space and adjusts the crossover and mutation rates in order to achieve fast convergence and high accuracy. And the new crossover operator is only search the space around better parent, which is a heuristic searching process. Experiments have been conducted to investigate the effectiveness of the proposed hysteresis identification approach.