Fault diagnosis for an automotive suspension using particle filters

D.H. Alcantara, R. Morales-Menendez, L. Amezquita-Brooks

Producción científica

5 Citas (Scopus)


To diagnose faults in automotive suspension systems a particle filters based approach was evaluated. The look-ahead Rao-Blackwell Particle Filter was tested to online monitor different oil leaks in a magneto-rheological shock absorber. The non-linear semi-active suspension was modelled through the Jump Markov Linear Gaussian framework. The feasibility of this approach has been analyzed in a simulation environment using different road profiles. Early results with high precision and low variance are promised; however, the computing time is a hard constraint for an online application.
Idioma originalEnglish
Título de la publicación alojada2016 European Control Conference, ECC 2016
Número de páginas6
ISBN (versión digital)9781509025916
EstadoPublished - 2016
Publicado de forma externa

Serie de la publicación

Nombre2016 European Control Conference, ECC 2016

All Science Journal Classification (ASJC) codes

  • Ingeniería de control y sistemas
  • Control y optimización


Profundice en los temas de investigación de 'Fault diagnosis for an automotive suspension using particle filters'. En conjunto forman una huella única.

Citar esto