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Title: Simulation-based optimum sensor selection design for an uncertain EMS system via Monte-Carlo technique
Authors: Michail, Konstantinos
Zolotas, Argyrios C.
Goodall, Roger M.
Keywords: Optimum sensor selection
Modern control design
EMS systems
Monte Carlo
Genetic algorithms
Issue Date: 2011
Publisher: © IFAC
Citation: MICHAIL, K. ... et al., 2011. Simulation-based optimum sensor selection design for an uncertain EMS system via Monte-Carlo technique. Proceedings of the 18th World Congress, Milan, Italy. The International Federation of Automatic Control, 2011, pp. 12650 - 12655.
Abstract: Optimum sensor selection in control system design is often a non-trivial task to do. This paper presents a systematic design framework for selecting the sensors in an optimum manner that simultaneously satisfies complex system performance requirements such as optimum performance and robustness to structured uncertainties. The framework combines modern control design methods, Monte Carlo techniques and genetic algorithms. Without losing generality its efficacy is tested on an electromagnetic suspension system via appropriate realistic simulations.
Description: This is a conference paper. It is also available at: http://www.ifac-papersonline.net/Detailed/51625.html
Version: Published
DOI: 10.3182/20110828-6-IT-1002.01224
URI: https://dspace.lboro.ac.uk/2134/9258
Publisher Link: http://dx.doi.org/10.3182/20110828-6-IT-1002.01224
ISBN: 9783902661937
Appears in Collections:Conference Papers and Presentations (Mechanical, Electrical and Manufacturing Engineering)

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