Lean and Steering Motorcycle Dynamics Reconstruction : An Unknown Input HOSMO Approach

Lamri Nehaoua 1 Dalil Ichalal 1 Hichem Arioui 1 Saïd Mammar 1 Leonid Fridman 2
1 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes
2 Sliding Mode Laboratory
Abstract : This paper deals with state estimation of Powered Two Wheeled (PTW) vehicle and robust reconstruction of related unknown inputs. For this purpose, we consider a unknown input high order sliding mode observer (UIHOSMO). First, a motorcycle dynamic model is derived using Jourdain's principle. In a second time, we consider both the observation of the PTW dynamic states, the reconstruction of the lean dynamics (roll angle φ(t)) and the rider's torque applied on the handlebar. Finlay, several simulation cases are provided to illustrate the efficiency of the proposed observer.
Keywords : Unknown input estimation Motorcycle Nonlinear State Observer Unknown input estimation.
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Conference papers
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Lamri Nehaoua, Dalil Ichalal, Hichem Arioui, Saïd Mammar, Leonid Fridman. Lean and Steering Motorcycle Dynamics Reconstruction : An Unknown Input HOSMO Approach. The American Control Conference (ACC 2013), Jul 2013, Washington, DC, United States. pp.2821--2826. ⟨hal-00786279⟩

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