A Sliding Mode Predictive Control-based Trajectory Tracking Algorithm for a Seabed Mining Vehicle

Seabed mining vehicles mostly work in thin and soft sediments, suffered from large external disturbance, so it is difficult to quickly converge the tracking error and accurately track the preset trajectory. A sliding mode predictive control-based (SMPC) trajectory-tracking algorithm is proposed in this study. First, based on the kinematic model of the mining vehicle, the trajectory-tracking error is quickly offset by a defined rule in the sliding mode control (SMC). Next, the rule is optimized by a linear time-varying model predictive control algorithm (LTV-MPC) with fewer predictive control steps. Here, the stability of the closed-loop control system is achieved. The joint simulation results of RecurDyn & Simulink show that compared with sliding mode control and linear time-varying model predictive control algorithm, the SMPC improves the trajectory-tracking accuracy and has good real-time performance.