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 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes
2 National Pol. Inst. of Mexico
3 Sliding Mode Laboratory

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: Motorcycle; High Order Sliding Mode; Strong Observability.; Strong Observability

Domains: Automatic

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, 2014, 63 (7), pp.3116--3127. ⟨10.1109/TVT.2014.2300633⟩. ⟨hal-00935371⟩