Optimized sensor configurations for a Maglev suspension system

Konstantinos, Michail, Zolotas, Argyrios and Goodall, Roger M. (2008) Optimized sensor configurations for a Maglev suspension system. Facta universitatis-series: Mechanics, Automatic Control and Robotics, 6 (1). pp. 169-184. ISSN 0354–2009

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Item Type:Article
Item Status:Live Archive


This paper discusses a systematic approach for selecting the minimum number of sensors for an Electromagnetic suspension system that satisfies both optimised deterministic and stochastic performance objectives. The performance is optimised by tuning the controller using evolutionary algorithms. Two controller strategies are discussed, an inner loop classical solution for illustrating the efficacy of the evolutionary algorithm and a Linear Quadratic Gaussian (LQG) structure particularly on sensor optimisation.

Additional Information:Volume 6, Special Issue, 2007
Keywords:sensor optimization, maglev suspensions, ems optimization, Genetic algorithms, Kalman filter, evolutionary algorithms
Subjects:H Engineering > H660 Control Systems
H Engineering > H332 Rail Vehicle Engineering
Divisions:College of Science > School of Engineering
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ID Code:24347
Deposited On:05 Oct 2016 13:37

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