Parameters identification of passive force control system based on backstepping genetic algorithm

To improve the identification accuracy of complex system, a genetic algorithm parameters identification method based on backstepping theory is proposed. First disassemble the passive force control system into input subsystem and output subsystem based on backstepping theory. Then identify parameter values of each subsystem using genetic algorithm method. And find the best mathematical model to approximate the real system with the goal that under the input of system the output of identification model approximates the output of real system. At last use another group of experiments data to test the efficiency of the identification parameters, and compare the result with the result of normal genetic algorithm parameters identification method. The result shows that the model which identified by proposed method can approximate the real system better, it not only meet the matching between input and output data sets, and to meet the matching between internal variables and output. This identification method can be used in the parameters identification of complex dynamic system.