Observer-based neural adaptive control of a platoon of autonomous tractor-trailer vehicles with uncertain dynamics

This study addresses the platoon formation control problem of multiple off-axle hitching tractor-trailers with limited communication ranges, under model uncertainties and external disturbances, without any collision and without velocity and acceleration measurements for the first time. Towards this end, a new second-order Euler-Lagrange formulation of tractor-trailers is introduced under the prescribed performance design procedure that preserves all structural properties of the tractor-trailer dynamics. Then, a prescribed performance non-linear transformation, a saturated filtered tracking error, radial basis function neural networks, an adaptive robust controller, and a high-gain observer are creatively employed to design a novel platoon output-feedback controller, which forces the vehicles to construct a desired convoy while guaranteeing the robust performance against unmodelled dynamics and external forces and ensuring inter-vehicular communication maintenance, collision avoidance between each successive pair in the convoy of vehicles, and some preassigned desired response specifications of platoon formation errors including overshoot/undershoot, convergence speed, and ultimate tracking accuracy. By utilising a Lyapunov-based stability analysis, a semi-global uniform ultimate boundedness of formation errors is ensured with prescribed performance. Finally, simulation results illustrate the efficacy of the proposed control system.