High-Order Fully Actuated System Approaches: Trajectory Tracking of AGVs Based on Model Predictive Control

Based on the high-order fully actuated (HOFA) system approaches, this paper proposes a method of trajectory tracking control for automated guided vehicles(AGVs) using two-layer cascade model predictive control with input saturation. First, We establish an under-actuated kinematic model of AGVs and transform it into a HOFA system. Subsequently, a cascaded model predictive control method is proposed by making full use of full-actuation property to eliminate the nonlinear kinematics of AGVs system. We design a predictive controller with a two-layer optimization structure and input saturation, which decouples the strongly coupled nonlinear system into distributed linear systems and solves the nonlinear constraint issues caused by nonlinear input transformations. The proposed AGV trajectory tracking controller reduces the optimization complexity and ensures the asymptotic stability of the corresponding closed-loop system. Finally, the effectiveness of the proposed AGV tracking control method is verified by simulation experiments.