Adaptive Super-Twisting Sliding Mode Control for Friction Compensation of Servo System Via AESO and Parameters Estimation

This paper presents a super-twisting sliding mode control strategy utilizing an adaptive extended state observer (AESO) for servo systems with nonlinear friction compensation to tackle the challenges of precise tracking. Firstly, an advanced online parameter identification mechanism is adopted to identify the unknown parameters of the continuous friction model within the system. This mechanism dynamically updates parameters in real-time, effectively converging to the true values of the parameters in response to the dynamic changes of the system. Subsequently, the AESO is employed to accurately estimate and compensate for the lumped disturbances, encompassing external disturbances and parameter estimation errors. Then, an adaptive super-twisting sliding mode controller is proposed. The controller is meticulously engineered to ensure the system's state accurately adheres to a predefined reference trajectory, effectively reducing errors stemming from model uncertainties and the influence of external disturbances. To empirically substantiate the efficacy of the proposed methods, a comprehensive series of simulation experiments are conducted, showcasing the superiority of the proposed method in terms of tracking accuracy and system stability.