Nonlinear Uncertainty Estimator-Based Robust Control for PMSM Servo Mechanisms With Prescribed Performance

Abstract

Active nonlinear uncertainties compensation is crucial for realizing high-precision servo control. However, the rejection of the unknown uncertainties is still a challenging problem. In view of these issues, this paper proposes a novel nonlinear uncertainty estimator based time-varying sliding mode control scheme for servo systems with prescribed performance. A nonlinear uncertainty estimator, which employs first-order low-pass filter operations with only one tuning parameter, is constructed to deal with unknown nonlinearities, while the NDE estimation error and uncertainties of the servo system are handled by the robust integral of the sign of the error (RISE) feedbacks. Meanwhile, a modified prescribed performance function (PPF) with a faster convergence rate is incorporated into the control design to restricted the tracking errors within the predefined asymptotic boundaries. By combining PPF and NDE, a time-varying sliding mode controller is developed to eliminate the reaching phase and improve the control performance. The validity and feasibility of the presented control scheme are verified with simulations and experiments based on a motor driving system.