Longitudinal speed control of a prototype vehicle via engine map identification and backstepping approach

In this paper, an experimental vehicle developed at the University of Trento, Italy is illustrated. For this vehicle, the raw data of the engine torque is estimated from the experimental longitudinal velocity and acceleration of the vehicle, obtained from a sequence of automated maneuvers. Then, a suitable polynomial parametrization of the engine torque map is presented, which allows for an elegant formulation of the least squares parameter identification. Finally, a control law based on a backstepping approach is proposed, that globally asymptotically stabilizes the nonlinear dynamics to the reference speed setpoint. The proposed control law is appealing because it induces a linear relation between the reference and the actual speed and its parameters can be tuned following a PD approach. Preliminary experimental results match somewhat the predicted behavior of the simulation analysis of the proposed controller.