Velocity Estimation Algorithms for Suspensions

Research output: Contribution to conferencePaper


Semi-active suspension systems aim to improve stability and comfort of vehicles. The most well-known semiactive suspension control strategies assume knowledge of the vehicle vertical-velocities. However, the vehicle normally does
not includes sensors for these variables. In this paper various vertical-velocities estimation algorithms are compared. First, the traditional filtered integration algorithm is revised; then a classical Luenberger observer is analyzed. An Unknown Input Observer (UIO) is also derived. Through UIO theory, it is shown that the unknown road profile induces observability problems. Finally,
a Kalman Filter is also evaluated. A comprehensive comparison between the estimation methods in several perturbation scenarios is performed. The results show that it is possible to archive good estimation performance with a low level of complexity using a combination of estimators.
Original languageEnglish
Publication statusAccepted/In press - 27 Aug 2019
Event7th IEEE Global Conference on Signal and Information Processing - SHAW Centre, Ottawa, Canada
Duration: 11 Nov 201914 Nov 2019
Conference number: 7


Conference7th IEEE Global Conference on Signal and Information Processing
Abbreviated titleGlobalSIP
Internet address

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    Hernandez-Alcantara, D. (Accepted/In press). Velocity Estimation Algorithms for Suspensions. Paper presented at 7th IEEE Global Conference on Signal and Information Processing, Ottawa, Canada.