title: Adaptive super-twisting observer for estimation of random road excitation profile in automotive suspension systems.
abstract: The estimation of road excitation profile is important for evaluation of vehicle stability and vehicle suspension performance for autonomous vehicle control systems. In this work, the nonlinear dynamics of the active automotive system that is excited by the unknown road excitation profile are considered for modeling. To address the issue of estimation of road profile, we develop an adaptive supertwisting observer for state and unknown road profile estimation. Under Lipschitz conditions for the nonlinear functions, the convergence of the estimation error is proven. Simulation results with Ford Fiesta MK2 demonstrate the effectiveness of the proposed observer for state and unknown input estimation for nonlinear active suspension system.
authors.affiliation: School of Electronics Engineering, Kyungpook National University, Daegu 702-701, Republic of Korea.
authors.forename: J J
authors.initials: JJ
authors.lastname: Rath
authors.affiliation: School of Electronics Engineering, Kyungpook National University, Daegu 702-701, Republic of Korea.
authors.forename: K C
authors.initials: KC
authors.lastname: Veluvolu
authors.affiliation: LAMIH, CNRS UMR 8201, University Lille Nord de France, UVHC, 59313 Valenciennes, France.
authors.forename: M
authors.initials: M
authors.lastname: Defoort
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001336:Automobiles; D003198:Computer Simulation; D017076:Computer-Aided Design; D004867:Equipment Design; D019544:Equipment Failure Analysis; D015233:Models, Statistical; D009991:Oscillometry / Q000379:methods*; D014186:Transportation / Q000295:instrumentation*