Direct identification for the continuous models of servo systems with friction nonlinearity

In order to describe precisely the dynamics and friction nonlinearity of servo systems, a novel direct identification method for nonlinear continuous model is proposed. The sampled input-output data and logic data corresponding to the velocity direction are chosen as the identification data. Through equivalent transformation, the unknown parameters are removed to the linear part of the model. Then the identification method based on state variable filter is utilized to determine the unknown parameters. Subsequently, the nonlinear continuous model of the servo system is obtained. The effectiveness of the proposed method is demonstrated by simulations and identification experiments on the two axis servo table. Both the simulations and experimental results show that, with the proposed method, the accurate nonlinear continuous model can be obtained even under sensor noises, which gives an accurate description of the system dynamics.