Model Predictive Lateral Control for Unmanned Ground Vehicles With Speed Coupling: A Terminal Constraint-Free Approach

In this article, a speed coupled lateral strategy is developed to enhance the tracking accuracy of unmanned ground vehicles (UGVs) with variable speed. The characteristics of UGVs are described in a linear parameter-varying (LPV) path-following model, where the speed variation is treated as parameter perturbation. Based on this, a model predictive control (MPC) algorithm is put forward to calculate the desired angular velocity as the upper control input. Moreover, in order to obtain the steering wheel angle driving UGVs, an appurtenant convertor based on kinematic model is designed for the transformation of control signals. The recursive feasibility of MPC is guaranteed via a terminal constraint-free approach, while its stability is deduced through min-max approach. Finally, several experiments are conducted to demonstrate the superiority of speed coupled lateral strategy.

Automated summary

This article develops a speed coupled lateral strategy to improve the tracking accuracy of unmanned ground vehicles (UGVs) with variable speed. The characteristics of UGVs are described using a linear parameter-varying (LPV) path-following model, where speed variation is treated as parameter perturbation. The proposed model predictive control (MPC) algorithm calculates the desired angular velocity as the upper control input. Additionally, a convertor based on kinematic model is designed to obtain the steering wheel angle for UGVs. The recursive feasibility of MPC is guaranteed using a terminal constraint-free approach, while stability is deduced through a min-max approach. Experimental results demonstrate the superiority of the speed coupled lateral strategy.