Research On Parameter Identification Algorithm Of AC Servo System Based On Hammerstein Model

Most of the industrial systems have non-linear characteristics.With the improvement of requirements of control precision in modern industry,using linear model fitting non-linear systems can no longer meet the requirements of control,the modeling of non-linear systems has gradually became an important direction of research.In this paper,Hammerstein model with simple and flexible structure is selected as the research model.The traditional identification algorithm,improved particle swarm optimization algorithm and improved firefly algorithm have been used to identify the Hammerstein model parameters.At last,The improved group intelligent optimization algorithm is used to identify the Hammerstein model of AC servo system.The main contents of this paper are as follows:Firstly,the parameters of Hammerstein model are identified by iterative method and recursive method in the traditional identification algorithm.The mathematical forms of iterative method and recursive method in Hammerstein model identification are deduced,and identification experiments are carried out on Hammerstein model under different noise intensities.The experimental results show that the two identification algorithms are effective in Hammerstein model identification,but there are some disadvantages such as low accuracy and identification accuracy affected by noise interference.Secondly,an improved PSO algorithm is proposed for parameter identification of Hammerstein model.This paper presents a strategy based on the population of the degree of polymerization of inertia weight adjustment and adaptive Levy mutation to improve the inertia weight coefficient and population variation of PSO algorithm,the standard numerical test cases of the simulation results show that the improved algorithm of Hammerstein model identification effect is better.Then,an improved FA algorithm is proposed for parameter identification of Hammerstein model.Aiming at two important parameters of FA algorithm,step size and attractiveness,variable step size and dynamic attractiveness strategy are proposed to improve FA algorithm,and improved FA algorithm is used to identify parameters of Hammerstein model.Simulation results of standard numerical test cases show that the improved algorithm has better identification effect than FA algorithm,and it has advantages and disadvantages compared with PSO algorithm.Therefore,an appropriate identification algorithm can be selected according to the performance index.Finally,The improved group computerization method is adopted to identify the Hammerstein model of ac servo system.The servo system model structure and common nonlinear characteristics are analyzed,the simulation model and Hammerstein model of the servo system are established,and Hammerstein model identification method is used to identify the Hammerstein model of the servo system.Experimental results show that the improved algorithm had a significant improvement in Hammerstein model identification of ac servo system.