Sliding Mode Control and Its Applications in Robot Trajectory Tracking Control: Review

Abstract

Sliding Mode Control (SMC), renowned for its robustness and anti-interference capabilities, is extensively applied in the realm of robot trajectory tracking. This paper reviews the application of SMC in robot trajectory tracking, and compares the performance differences between traditional SMC and improved SMC (including integral sliding mode control ISMC and adaptive neural network sliding mode control ANNSMC). Although traditional SMC is widely used in robot trajectory tracking due to its strong robustness, its high-frequency jitter problem cannot be ignored. In contrast, ISMC effectively reduces the system steady-state error, improves control accuracy and alleviates jitter by introducing an integral term. ANNSMC merges the nonlinear mapping capabilities of neural networks with the resilience of SMC, significantly enhancing trajectory tracking precision. This paper seeks to offer readers a comprehensive view of sliding mode control's application in robot trajectory tracking. It delivers a thorough evaluation of the strengths and weaknesses of different methods, serving as a valuable reference for future research.