Actuator hysteresis identification and compensation using an adaptive search space based genetic algorithm

A proposed genetic algorithm with adaptive search space (GAASS) is applied to identify the hysteresis parameters of an electromechanical-valve actuator installed on a pneumatic pipeline 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. Experiments have been conducted to investigate the effectiveness of the proposed hysteresis identification and compensation approach with three different types of sensor measurements, and the results are reported in this paper.