Input-output feedback linearization control of a tractor with n-trailers mechanism considering the path curvature

In this paper, an observer-based proportional-integral-derivative (PID) controller is proposed for an autonomous tractor with n-trailer units with prescribed transient and steady-state performances by compensating the negative effect of the path curvature during the turning of the trailers. The control objective is to place the position of the last trailer on a desired trajectory without any deviation in the course of its turning. Since the curvature of the trajectory causes a remarkable unwanted deviation of the trailers' positions from the path, an input-output model is derived for the tractor with n-trailers based on the extended look-ahead control concept which employs a corrective angle to compensate the path curvature. A nonlinear transformation is employed to transform constrained errors into unconstrained ones and to obtain an open-loop error dynamic model in terms of the unconstrained errors. Then, a neural network adaptive PID output-feedback linearization-based controller is proposed to force the tracking errors to the zero neighbourhood with a guaranteed prescribed performance with preferable overshoot/undershoot, convergence speed and final tracking accuracy. The Kalman-Yakobovich (KY) lemma is employed to prove the closed-loop stability of the observer-controller system strongly. Numerical simulations are given to show the controller's effectiveness in practice.

Automated summary

In this paper, an observer-based PID controller is proposed to improve the transient and steady-state performance of an autonomous tractor with multiple trailer units. By compensating for the negative effect of path curvature during trailer turning, the controller aims to keep the last trailer on a desired trajectory without deviation. The control strategy involves model derivation, nonlinear transformation, and neural network adaptive PID control, ensuring fast convergence and high accuracy of tracking errors.