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.
|Title of host publication||2016 European Control Conference, ECC 2016|
|Number of pages||6|
|Publication status||Published - 6 Jan 2017|
|Name||2016 European Control Conference, ECC 2016|
Bibliographical notePublisher Copyright:
© 2016 EUCA.
Copyright 2017 Elsevier B.V., All rights reserved.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Control and Optimization