Observer‐based neural adaptive control of a platoon of autonomous tractor–trailer vehicles with uncertain dynamics
Omid Elhaki, Khoshnam Shojaei
Abstract
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.