Research On Nonlinear Compensation Algorithm For Turntable Servo System

Friction and backlash are the two major nonlinear interference factors in the servo system. The existence of friction and backlash is likely to cause low-velocity crawl, driver-delay, limit cycle oscillations and other issues affecting the system tracking accuracy. The researchers always ignore some unimportant interference factors and only compensate a main nonlinearity. In some practical application, this method has achieved a certain effect. However, in the actual system, the influence of friction and backlash coexists and interacts. In a high precision servo system, if the controller is designed to compensate only a single nonlinear factor, system performance will be difficult to meet the desired requirements. Based on the above discussion, this paper introduces a compensation control method of the turntable servo system with friction and backlash. The main contents are as follows:Firstly, considered structure characteristics of the turntable servo system, a servo system model with nonlinear friction and backlash is established. Especially, focusing on the instability of traditional LuGre model, an improved friction model is given.Secondly, in order to suppress the influence of friction in servo system, a sliding mode controller is designed, which can enhance the anti-interference ability of the system. Simulation results show that the sliding mode control algorithm can suppress the friction disturbance.Thirdly, a class of servo system with nonlinear backlash is researched. By introducing an approximation "dead zone" function, a back-stepping controller is designed, which is based on the feedback of state variables. Compared with the PID control, simulation results verify that the back-stepping control can suppress the influence of backlash effectively.Fourthly, for the servo system with unknown friction and backlash, a back-stepping sliding mode controller is designed. An adaptive neural network(RBF) algorithm is used to estimate the nonlinearity including friction and backlash. The stability of system is proved by selecting an appropriate Lyapunov function. Besides, simulation results verify that the control strategy can overcome the influence of friction and backlash. Simultaneously, it can improve the tracking precision significantly.