Velocity Estimation Algorithms for Suspensions

DIana Hernandez-Alcantara, Luis Amezquita-Brooks, Nancy Morales-Villarreal, Omar A. Juarez-Tamez

Research output: Contribution to conferencePaperpeer-review

Abstract

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
DOIs
Publication statusPublished - 1 Nov 2019
Event7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019 - Ottawa, Canada
Duration: 11 Nov 201914 Nov 2019

Conference

Conference7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019
CountryCanada
CityOttawa
Period11/11/1914/11/19

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Information Systems and Management
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing

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