Position Synchronization Control Strategy for Dual-Motor Load Drive System

This paper presents a repeated learning based adaptive sliding mode control (RL-APSMC) approach for achieving high-performance control in a dual-motor load drive system. Unlike conventional sliding mode control (SMC), RL-APSMC enhances synchronization by continuously learning and compensating for synchronization uncertainties between motors, thereby improving system performance. The adaptive law is employed to estimate the system's unknown inertia parameters, which are then fed back in real time to the position tracking controller designed with a sliding surface, ensuring accurate position tracking. This study derives the mathematical model of the dual-motor drive system, provides a detailed explanation of the RL-APSM C design process, and rigorously proves its stability. Simulation results demonstrate that RL-APSMC outperforms traditional SMC in both tracking accuracy and synchronization, making it more suitable for dual-motor load drive applications.