Unknown input observer for vehicle lateral dynamics based on a Takagi-Sugeno model with unmeasurable premise variables

Zedjiga Yacine , Dalil Ichalal , Naima Ait Oufroukh , Saïd Mammar , Said Djennoune

In this paper, an observer is proposed for estimating vehicle states which are not available for measurement. A new representation of a nonlinear vehicle model by exact Takagi-Sugeno structure is proposed based on sector nonlinearity approach. It leads to a multiple model with unmeasurable premise variables which constitutes the first contribution of the present paper. As a second contribution, a state estimation by an Unknown Input Observer (UIO) with unmeasurable premise variables is considered. It takes into account the variations of the longitudinal velocity in order to reflect realistic driving conditions. The convergence conditions of this observer are formulated as an optimization problem subjected to constraints established using Lyapunov theory and expressed under Linear Matrix Inequalities. Finally, some simulations are performed on the nonlinear model of the vehicle including the variations of the longitudinal velocity.

Keywords: Convergence conditions; Driving conditions; Longitudinal velocity; Lyapunov theories; Multiple models; Non-linear model; Optimization problems; Sector nonlinearity; Takagi-sugeno; Takagi-Sugeno models; Unknown input observer; Vehicle lateral dynamics; Vehicle model; Vehicle state

Domains: Engineering Sciences [physics]; Automatic

Zedjiga Yacine, Dalil Ichalal, Naima Ait Oufroukh, Saïd Mammar, Said Djennoune. Unknown input observer for vehicle lateral dynamics based on a Takagi-Sugeno model with unmeasurable premise variables. 51st IEEE Conference on Decision and Control (CDC 2012), Dec 2012, Maui, United States. pp.6211--6216, ⟨10.1109/CDC.2012.6426213⟩. ⟨hal-00905748⟩