Integration of Model Predictive Control and Proportional–Integral–Derivative Strategies for the Autonomous Path Tracking of Agricultural Wide-Span Implement Carriers

Abstract

This paper presents a path-tracking control algorithm for the autonomous operation of agricultural wide-span implement carriers (WSICs). A WSIC is a versatile power unit consisting of a long truss supported and operated by vehicles at both ends, which minimizes soil compaction and traffic-induced damage to crops in controlled-traffic farming systems. The proposed algorithm combines model predictive control (MPC) and proportional–integral–derivative (PID) control strategies to achieve precise and accurate path tracking for the supporting vehicles. We present a dynamic model of the WSIC, design control systems for the supporting vehicles, and establish control laws for path tracking. The methodology employs kinematic differential geometry for deriving motion parameters, MPC for steering angle control, and PID for velocity control. The control algorithms account for wheel slip, external forces and moments, and other interactions experienced by the WSIC under field operating conditions. Our simulations demonstrate that under the designed steering angle and velocity control, the control strategies can effectively correct lateral and orientation deviations of each vehicle and offset errors between the two vehicles. The next phase of this research work will involve the experimental validation of the control algorithms using a scaled-down robotic WSIC platform. This research contributes to the field of autonomous agricultural vehicles by addressing the challenges of path tracking for WSICs. The proposed algorithm can potentially improve agricultural operations and reduce overlaps and misses.