An Unknown Input HOSM Approach to Estimate Lean and Steering Motorcycle Dynamics

Lamri Nehaoua 1 Dalil Ichalal 1 Hichem Arioui 1 Jorge Davila 2 Saïd Mammar 1 Leonid Fridman 3
1 SIBI
IBISC - Informatique, Biologie Intégrative et Systèmes Complexes
2 National Pol. Inst. of Mexico
Sliding Mode Laboratory
3 Sliding Mode Laboratory
Abstract : This paper deals with state estimation of Powered Single-Track vehicle and robust reconstruction of related unknown inputs. For this purpose, we consider an unknown input high order sliding mode observer (UIHOSMO). First, a motorcycle dynamic model is derived using Jourdain's principle. The strong observability of the obtained model is illustrated. Then, we consider both the observation of the PTW dynamic states and the reconstruction of the lean dynamics and the rider's torque applied on the handlebar. Finally, several simulation cases are provided to illustrate the efficiency of the observer.
Keywords : Strong Observability Motorcycle High Order Sliding Mode Strong Observability.
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Article dans une revue
IEEE Transactions on Vehicular Technology, Institute of Electrical and Electronics Engineers, 2014, 63 (7), pp.3116--3127. 〈10.1109/TVT.2014.2300633〉
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Dernière modification le : jeudi 9 février 2017 - 15:51:03
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Lamri Nehaoua, Dalil Ichalal, Hichem Arioui, Jorge Davila, Saïd Mammar, et al.. An Unknown Input HOSM Approach to Estimate Lean and Steering Motorcycle Dynamics. IEEE Transactions on Vehicular Technology, Institute of Electrical and Electronics Engineers, 2014, 63 (7), pp.3116--3127. 〈10.1109/TVT.2014.2300633〉. 〈hal-00935371〉

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