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Conference Papers Year : 2017

PI observer robust fault estimation for motorcycle lateral dynamics

Abstract

This paper is devoted to the robust fault detection and estimation for the lateral dynamics of a motorcycle. The later is modelled using an uncertain switched system formalism. A switched proportional integral observer is designed in order to minimize the effect of the disturbance and uncertainties on residual sensitivity. It consists in the design of proportional integral observer which minimizes the well-known H∞ norm and ensures Input-to-State-Stability (ISS). The problem is formulated as a linear matrix inequalities (LMI) feasibility problem in which a cost function is minimized subject to LMI constraints. Various estimation problems are considered including state estimation, unknown input estimation and non-linear dynamics behaviour estimation which is considered as a fault input. A set of simulation studies are provided in order to establish the validity of the approach which allows sensor less implementation of driving assistance systems for motorcycles.
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Dates and versions

hal-01585804 , version 1 (12-09-2017)

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Cite

Dalil Ichalal, Naima Ait Oufroukh, Pierre-Marie Damon, Hichem Arioui, Saïd Mammar. PI observer robust fault estimation for motorcycle lateral dynamics. 14th IEEE International Conference on Networking, Sensing and Control (ICNSC 2017), May 2017, Calabria, Italy. pp.127--132, ⟨10.1109/ICNSC.2017.8000079⟩. ⟨hal-01585804⟩
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