A Model Predictive approach for semi active suspension control problem of a full car

Manh Quan Nguyen (1) , Massimo Canale (2) , Olivier Sename (1) , Luc Dugard (1)

1 GIPSA-SLR - GIPSA - Systèmes linéaires et robustesse
2 DAUIN - Dipartimento di Automatica e Informatica [Torino]

A suspension controller aims at enhancing the ride comfort and the handling of vehicle which are evaluated by the acceleration at center of gravity and the roll motion respectively. In this paper, a semi-active suspension Model Predictive Control (MPC) is designed for a full vehicle system equipped with 4 semi-active dampers. The main challenge in the semi-active suspension control problem is to tackle with the dissipativity constraints of the semi-active dampers, here recasted as input and state constraints. The controller is designed in the MPC framework where the effects of the unknown road disturbances are taken into account. An observer approach allows to estimate the road disturbance information to be used by the controller during the prediction step. Then, the MPC control law with road estimation (but without road preview) is computed by minimizing a quadratic cost function, giving a trade-off between the comfort and the handling, while guaranteeing some physical constraints of the semi-active dampers. Some simulation results performed on a nonlinear full car model are presented in order to illustrate the effectiveness of the proposed approach.

Mots clés: Input Constraints; Semi-active suspension; road disturbance estima-tion; MPC control

Domaines: Automatique / Robotique

Manh Quan Nguyen, Massimo Canale, Olivier Sename, Luc Dugard. A Model Predictive approach for semi active suspension control problem of a full car. CDC 2016 - 55th IEEE Conference on Decision and Control, Dec 2016, Las Vegas, NV, United States. pp. 721 - 726, ⟨10.1109/CDC.2016.7798353⟩. ⟨hal-01361841⟩