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Title: Fallback options for airgap sensor fault of an electromagnetic suspension system
Authors: Michail, Konstantinos 
Zolotas, Argyrios C. 
Goodall, Roger M. 
Major Field of Science: Engineering and Technology
Field Category: Mechanical Engineering
Keywords: Maglev;Active suspensions;Airgap sensor fault;Kalman estimator;Genetic algorithms
Issue Date: 2013
Source: Central European Journal of Engineering, 2013, vol. 3, no. 2, pp. 206-220
Volume: 3
Issue: 2
Start page: 206
End page: 220
Journal: Central European Journal of Engineering 
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.
ISSN: 2081-9927
DOI: 10.2478/s13531-012-0060-y
Rights: © De Gruyter
Type: Article
Affiliation : Cyprus University of Technology 
University of Sussex 
Loughborough University 
Appears in Collections:Άρθρα/Articles

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