Optimal Trajectory Tracking Control for Automated Guided Vehicles

Abstract

This work presents a control strategy for the trajectory tracking problem of an Automated Guided Vehicle (AGV). In contrast to the current methods, this design strategy remains invariant and flexible to arbitrary number of wheels. A three-stage cascade control strategy is proposed in which the control design for the vehicle chassis is separated from the wheel-tire modules. For a given vehicle reference trajectory, the outer controller determines the required forces and moment inputs to the vehicle chassis in a time-receding fashion. At the second stage, the required forces and moment inputs are optimally allocated for each wheel and tire. At each wheel-tire module, a nonlinear controller is used to determine the actual control input for the wheel actuators. The performance of the presented control strategy is illustrated through simulation results with a realistic driving scenario for a six-wheeled vehicle. We demonstrate that the proposed controller architecture is configurable for an arbitrary number of wheels and capable of handling large steering angles efficiently.