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Robust estimation of vehicle lateral velocity and yaw rate using switched T-S fuzzy interval observers

Abstract : This paper presents a new robust estimation of the lateral velocity and yaw rate using switched Takagi-Sugeno fuzzy interval observers. The longitudinal velocity is treated as the online measured time-varying parameter and the cornering stiffness at front and rear tires are assumed to be unknown but bounded with a priori known bounds. Based on a multiple model switching structure, this design divides the range of variation of the longitudinal velocity into a finite number of adjoint regions and, accordingly, develops multiple interval observers for the multiple model set. The switching law which is assumed to be available online selects automatically the appropriate candidate estimator, according to the operation sub-region. Applying the proposed set-approach to estimate the lateral vehicle dynamics allows to cope with uncertainties and ensures guaranteed bounds on the lateral velocity and yaw rate despite changes in tire/road and driving conditions. Sufficient conditions for the existence of the robust proposed observer are expressed in terms of Linear Matrix Inequalities through the use of a switched fuzzy ISS-Lyapunov function. Simulations based on experimental data demonstrate the effectivenesses of the proposed approach.
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Submitted on : Friday, April 6, 2018 - 10:21:20 PM
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Sara Ifqir, Naima Ait Oufroukh, Dalil Ichalal, Saïd Mammar. Robust estimation of vehicle lateral velocity and yaw rate using switched T-S fuzzy interval observers. 2017 IEEE International Conference on Systems, Man and Cybernetics (SMC 2017), Oct 2017, Banff, Canada. pp.3249--3254, ⟨10.1109/SMC.2017.8123129⟩. ⟨hal-01760972⟩



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