Semi-active suspension systems aim to improve stability and comfort of vehicles. The most well-known semi-active 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: the traditional filtered integration algorithm, the classical Luenberger observer, the Unknown Input Observer and the Kalman Filter. 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.
|Publication status||Published - 1 Nov 2019|
|Event||7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019 - Ottawa, Canada|
Duration: 11 Nov 2019 → 14 Nov 2019
|Conference||7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019|
|Period||11/11/19 → 14/11/19|
Bibliographical notePublisher Copyright:
© 2019 IEEE.
Copyright 2020 Elsevier B.V., All rights reserved.
All Science Journal Classification (ASJC) codes
- Information Systems
- Information Systems and Management
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Signal Processing