Articolo in rivista, 2020, ENG, 10.1016/j.ifacol.2020.12.1440

Active attitude control of ground vehicles with partially unknown model

Bianchi, D.; Borri, A.; Di Benedetto, M. D.; Di Gennaro, S.

Consiglio Nazionale delle Ricerche; Università degli Studi dell'Aquila; University of G. d'Annunzio Chieti and Pescara

We present a novel solution to the attitude control problem of ground vehicles by means of the Active Front Steering (AFS) system. The classical feedback linearization method is often used to track a reference yaw dynamics while guaranteeing vehicle stability and handling performance, but it is difficult to apply because it relies on the exact knowledge of the nonlinearities of the vehicle, in particular the tire model. In this work, the unknown nonlinearities are real-time learnt on the basis of the universal approximation property, widely used in the area of neural networks. With this approximation method, the Uniform Ultimate Boundedness (UUB) property with respect to tracking and estimation errors can be formally proven. Preliminary simulation results show good tracking capabilities when model and parameters are affected by uncertainties, also in presence of actuator saturation.

IFAC-PapersOnLine 53 (2), pp. 14420–14425

Keywords

Automotive control, Learning, Neural networks, Nonlinear control, Uncertain systems

CNR authors

Borri Alessandro

CNR institutes

IASI – Istituto di analisi dei sistemi ed informatica "Antonio Ruberti"