Path-following control method for articulated vehicles based on dual heuristic programming

Abstract

A path-following control method based on dual heuristic programming (DHP) is proposed to address the problem whereby unmanned articulated vehicles need to set different controller parameters to track complex routes and cannot adapt to complex routes. First, the path-following control system structure is designed based on the articulated vehicle experimental platform, and the error model is derived based on the kinematic model of the articulated vehicle. Second, the payoff function is designed considering the error and stability indices, and the actor and critic of the path-following control method based on the DHP algorithm are approximated using a multilayer feedforward neural network. Finally, the path-following quality of the method is verified using simulations and real vehicle tests and compared with the conventional pure tracking and linear-quadratic regulator methods. The results show that the DHP-based method is able to follow complex reference paths and obtain better control results than the traditional methods without iterative tuning of the controller parameters, which improves the adaptiveness of the articulated vehicle path-following control method to complex environments.