Parametric identification of a powered two-wheeled vehicles : Algebraic approach

Fouka, Majda; Damon, Pierre-Marie; Nehaoua, Lamri; Arioui, Hichem; Mammar, Saïd

doi:10.1109/med.2017.7984256

Cited by 4 publications

(1 citation statement)

References 14 publications

(17 reference statements)

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“…It is sometimes very difficult to measure some of these parameters like the inertia. In this case, identification approaches as in [7] can be used to determine the corresponding parameters. Hence, in addition to the intrinsic complexity, the difficulty to identify all the needed parameters make them not adapted for ARAS design but very useful tools to proceed in a first validation of ARAS before testing them on real vehicles.…”

Section: Motivation and Contextmentioning

confidence: 99%

Steering and Lateral Motorcycle Dynamics Estimation: Validation of Luenberger LPV Observer Approach

Damon

Ichalal

Arioui

2019

IEEE Trans. Intell. Veh.

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In this paper a validation of the Luenberger-like nonlinear observer, proposed in one of our recent work, is performed by means of a commercial motorcycle simulator. The previous paper has introduced the design of a nonlinear Luenberger observer to simultaneously estimate both the motorcycle lateral dynamics and the rider action. The vehicle lateral motion is described with a two-body linear model which takes into account the longitudinal speed variation as a time-varying parameter. Then, the Takagi-Sugeno approach combined to the Lyapunov theory, linear matrix inequalities tools and L 2-gain property are used to demonstrate the observer's convergence through an input-to-error stability. Finally, the effectiveness and the robustness of the observer are tested on three different realistic riding scenarios by means of the well-know multibody simulator BikeSim. Finally, the estimation performances are compared to previous works.

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Section: Motivation and Contextmentioning

confidence: 99%

Steering and Lateral Motorcycle Dynamics Estimation: Validation of Luenberger LPV Observer Approach

Damon

Ichalal

Arioui

2019

IEEE Trans. Intell. Veh.

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Adaptive Observer for Motorcycle State Estimation and Tire Cornering Stiffness Identification

Fouka¹,

Nehaoua²,

Dabladji³

et al. 2018

2018 IEEE Conference on Decision and Control (CDC)

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In this paper, a linear parameter varying (LPV) adaptive observer is designed for state estimation and tire cornering stiffness identification based on lateral motorcycle model. The estimation is based on a general Lipstchitz condition, Lyapunov function and is subjected to persistency of excitation conditions. Further, the LPV observer is transformed into Takagi-Sugeno (T-S) fuzzy observer and sufficient conditions, for the existence of the estimator, are given in terms of linear matrix inequalities (LMIs). This method is designed assuming that some of the states are not available, since parametric identification is generally developed assuming that all the system states are available (measured or estimated). Finally, the effectiveness of the proposed estimation method is illustrated through test scenarios performed with the wellknown motorcycle simulator "BikeSim" and by field test using data measurement carried out on experimental motorcycle.

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Road Geometry and Steering Reconstruction for Powered Two Wheeled Vehicles

Fouka

Nehaoua

Ichalal

et al. 2018

2018 21st International Conference on Intelligent Transportation Systems (ITSC)

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This paper deals with the estimation of both motorcycle lateral dynamics and road geometry reconstruction. A linear parameter varying (LPV) unknown input observer is designed to estimate the whole motorcycle dynamic states including road banking angles and the rider's steering torque taken into account the variation of the forward velocity. The road bank angle and the lateral slip angle are relevant parameters for improving rider's safety and handling, thus, it is interesting to estimate the road geometry. The observer convergence study is based on Lyapunov theory and the established convergence conditions are expressed in linear matrix inequalities (LMIs) formalism. The main idea consists in getting a set of conditions to design an observer transformed into a polytopic form, which estimates a part of the motorcycle dynamics states independently of some inputs (rider torque) and/or other states (zeros dynamics: roll angle) taken into account the variation of the longitudinal velocity. Simulation results of experimental test are provided to confirm the efficiency of the proposed design method.

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Parametric identification of a powered two-wheeled vehicles : Algebraic approach

Cited by 4 publications

References 14 publications

Steering and Lateral Motorcycle Dynamics Estimation: Validation of Luenberger LPV Observer Approach

Steering and Lateral Motorcycle Dynamics Estimation: Validation of Luenberger LPV Observer Approach

Adaptive Observer for Motorcycle State Estimation and Tire Cornering Stiffness Identification

Road Geometry and Steering Reconstruction for Powered Two Wheeled Vehicles

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