Iterative Learning enhanced Integral Terminal Sliding Mode Control for Precision Motion Systems

The rapid development and applications of precision motion systems pose a great challenge on tracking performance improvement to complete various industrial or scientific tasks. In this paper, an iterative learning enhanced integral terminal sliding mode control (IL- ITSMC) is developed to further enhance the performance of such systems under repetitive trajectory and disturbance. For the generally used second-order model in precision motion systems, an integral terminal sliding surface is utilized to improve the steady-state performance and robustness to unexpected disturbance. A novel reaching law is also designed to realize the finite-time convergence of the sliding surface. In addition, an iterative learning law is proposed based on the sliding surface to compensate the repetitive term through updating the feedforward control input iteratively. The stability in time domain and convergence in iterative domain are proven theoretically based on the well-known Lyapunov theory, respectively. The simulation results on a pizeo-actuated stage with hysteresis nonlinearity demonstrate that the proposed IL-ITSMC achieves the best tracking performance through comparisons, and the convergence speed is improved significantly in comparison with ITSMC with traditional P-type ILC (PIL- ITSMC) for a 10Hz sinusoidal repetitive trajectory.