Adaptive Super-Twisting Observer for Estimation of Random Road Excitation Profile in Automotive Suspension Systems

Jagat Jyoti Rath (1) , Kalyana Chakravarthy Veluvolu (1) , Michael Defoort (2)

1 KNU - Kyungpook National University [Daegu]
2 LAMIH - Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201

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.

Domaines: Automatique / Robotique

Jagat Jyoti Rath, Kalyana Chakravarthy Veluvolu, Michael Defoort. Adaptive Super-Twisting Observer for Estimation of Random Road Excitation Profile in Automotive Suspension Systems. The Scientific World Journal, 2014, 2014, pp.ID 203416. ⟨10.1155/2014/203416⟩. ⟨hal-03644639⟩