Distributed nonlinear model predictive control of an autonomous tractor-trailer system

TL;DR

This paper presents a fast distributed nonlinear model predictive control method combined with nonlinear moving horizon estimation to achieve precise and robust trajectory tracking for autonomous tractor-trailer systems, accounting for constraints and disturbances.

Contribution

It introduces a novel control and estimation framework that enhances trajectory tracking accuracy and robustness for autonomous tractor-trailers under constraints.

Findings

High control accuracy demonstrated in simulations

Robustness against environmental disturbances confirmed

Effective constraint handling in control design

Abstract

This paper addresses the trajectory tracking problem of an autonomous tractor-trailer system by using a fast distributed nonlinear model predictive control algorithm in combination with nonlinear moving horizon estimation for the state and parameter estimation in which constraints on the inputs and the states can be incorporated. The proposed control algorithm is capable of driving the tractor-trailer system to any desired trajectory ensuring high control accuracy and robustness against environmental disturbances.