Etude préliminaire d'une commande sans modèle pour papillon de moteur

Join, Cédric; Masse, John; Fliesś, Michel

doi:10.3166/jesa.42.337-354

Cited by 30 publications

(20 citation statements)

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“…Let us emphasize finally that the practical usefulness in the automotive industry of these new algebraic techniques is confirmed by other successful applications (Abouaissa, Fliess, & Join, 2008;d'André a-Novel et al, 2010;Join, Masse, & Fliess, 2008;Villagra et al, 2009Villagra et al, , 2008aVillagra et al, , 2008b.…”

Section: Discussionmentioning

confidence: 90%

A diagnosis-based approach for tire–road forces and maximum friction estimation

Villagrá

d’Andréa-Novel

Fliess

et al. 2011

Control Engineering Practice

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113

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a b s t r a c tA new approach to estimate vehicle tire forces and road maximum adherence is presented. Contrarily to most of the previous works on this subject, it is not an asymptotic observer-based estimation, but a combination of elementary diagnosis tools and new algebraic techniques for filtering and estimating derivatives of noisy signals. In a first step, instantaneous friction and lateral forces will be computed within this framework. Then, extended braking stiffness concept is exploited to detect which braking efforts allow to distinguish a road type from another. A weighted Dugoff model is used during these 'distinguishable' intervals to estimate the maximum friction coefficient. Very promising results have been obtained in noisy simulations and real experimentations for most of the driving situations.

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Section: Discussionmentioning

confidence: 90%

A diagnosis-based approach for tire–road forces and maximum friction estimation

Villagrá

d’Andréa-Novel

Fliess

et al. 2011

Control Engineering Practice

Self Cite

113

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“…An algebraic approach is under study to generate the physical control variables: the throttle angle (see already [8]) and brake pressure. Furthermore, the whole algorithm is being adapted to real vehicles and will be soon presented.…”

Section: Discussionmentioning

confidence: 99%

Robust grey-box closed-loop stop-and-go control

Villagrá

d’Andréa-Novel

Fliess

et al. 2008

2008 47th IEEE Conference on Decision and Control

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Abstract-This paper presents a robust stop-and-go control law, especially well adapted to car following scenarios in urban environments. Since many vehicle/road interaction factors (road slope, rolling resistance, aerodynamic forces) are very poorly known and measurements are quite noisy, a robust strategy is proposed within an algebraic framework. 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 closed-loop control will be implemented to compensate all kind of unmodeled dynamics or parameter uncertainties.

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“…Model-free control is a very recent approach to nonlinear control that has been introduced in [2], (Refer to [3] for a thorough presentation). A first industrial and convincing application is reported in [13].…”

Section: Summary Of Model-free Controlmentioning

confidence: 99%