Robust stop-and-go control strategy: an algebraic approach for nonlinear estimation and control

Abstract : This paper describes a robust stop-and-go control strategy for vehicles. Since sensors used in a real automotive context are generally low cost, measurements are quite noisy. Furthermore, many vehicle/road interaction factors (road slope, rolling resistance, aerodynamic forces) are very poorly known. Hence, a robust strategy to noise and parameters is proposed within the same theoretical framework: algebraic nonlinear estimation and control techniques. On the one hand, noisy signals will be processed in order to obtain accurate derivatives, and thereafter, variable estimates. On the other hand, a grey-box closedloop control will be implemented to reject all kind of disturbances caused by exogenous parameter uncertainties.
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https://hal.inria.fr/inria-00419445
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Submitted on : Friday, September 25, 2009 - 3:42:51 PM
Last modification on : Wednesday, March 27, 2019 - 4:41:26 PM
Long-term archiving on : Wednesday, September 22, 2010 - 1:33:13 PM

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Jorge Villagra, Brigitte d'Andréa-Novel, Sungwoo Choi, Michel Fliess, Hugues Mounier. Robust stop-and-go control strategy: an algebraic approach for nonlinear estimation and control. Int. J. Vehicle Autonomous Systems, Inderscience Publishers, 2009, 7 (3/4), pp.270-291. ⟨10.1504/IJVAS.2009.033264⟩. ⟨inria-00419445v2⟩

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