Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/8146
Title: Fallback options for airgap sensor fault of an electromagnetic suspension system
Authors: Michail, Konstantinos 
Zolotas, Argyrios C. 
Goodall, Roger M. 
Keywords: Maglev;Active suspensions;Airgap sensor fault;Kalman estimator;Genetic Algorithms
Category: Mechanical Engineering
Field: Engineering and Technology
Issue Date: 2013
Publisher: Springer
Source: Central European Journal of Engineering, Volume 3, Issue 2, Pages 206-220, 2013
Abstract: The paper presents a method to recover the performance of an electromagnetic suspension under faulty airgap sensor. The proposed control scheme is a combination of classical control loops, a Kalman Estimator and analytical redundancy (for the airgap signal). In this way redundant airgap sensors are not essential for reliable operation of this system. When the airgap sensor fails the required signal is recovered using a combination of a Kalman estimator and analytical redundancy. The performance of the suspension is optimised using genetic algorithms and some preliminary robustness issues to load and operating airgap variations are discussed. Simulations on a realistic model of such type of suspension illustrate the efficacy of the proposed sensor tolerant control method.
URI: http://ktisis.cut.ac.cy/handle/10488/8146
http://ktisis.cut.ac.cy/handle/10488/8146
http://hdl.handle.net/10488/8146
ISSN: 2081-9927
DOI: 10.2478/s13531-012-0060-y
Rights: © 2013 Springer
Type: Article
Appears in Collections:Άρθρα/Articles

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