Vehicle Lateral Dynamics Estimation using Switched Unknown Inputs Interval Observers: Experimental Validation

Sara Ifqir 1 Naima Ait Oufroukh 1 Dalil Ichalal 1 Saïd Mammar
1 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes
Abstract : A systematic design methodology for interval estimation of switched uncertain linear systems subject to uncertainties and unknown inputs is presented. The uncertainties under consideration are assumed to be unknown but bounded with a priori known bounds. The proposed observer is used to robustly estimate the vehicle yaw rate and lateral velocity using a vision system measurement. The road curvature is treated as an unknown input and a linear adaptive tire model is considered to take into account the changes of the road adhesion. Sufficient conditions allowing the design of such observer are derived using Multiple Quadratic ISS-Lyapunov function and an LMIs (Linear Matrix Inequalities) formulation is obtained. Performance of the algorithm is evaluated using vehicle real data, results show that the proposed estimation scheme succeeds to appropriately estimate the upper and lower bounds of vehicle lateral dynamics despite of the presence of unknown inputs.
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Sara Ifqir, Naima Ait Oufroukh, Dalil Ichalal, Saïd Mammar. Vehicle Lateral Dynamics Estimation using Switched Unknown Inputs Interval Observers: Experimental Validation. The 2018 American Control Conference (ACC 2018), Jun 2018, Milwaukee, WI, United States. pp.1138--1143, ⟨10.23919/ACC.2018.8431486⟩. ⟨hal-01744709⟩

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