  This paper addresses the trajectory tracking problem of an autonomous
tractor-trailer system by using a decentralized control approach. A fully
decentralized model predictive controller is designed in which interactions
between subsystems are neglected and assumed to be perturbations to each other.
In order to have a robust design, a tube-based approach is proposed to handle
the differences between the nominal model and real system. Nonlinear moving
horizon estimation is used for the state and parameter estimation after each
new measurement, and the estimated values are fed to robust tube-based
decentralized nonlinear model predictive controller. The proposed control
scheme is capable of driving the tractor-trailer system to any desired
trajectory ensuring high control accuracy and robustness against neglected
subsystem interactions and environmental disturbances. The experimental results
show an accurate trajectory tracking performance on a bumpy grass field.
