Simulation-based optimum sensor selection design for an uncertain EMS system via Monte-Carlo technique

Michail, Konstantinos and Zolotas, Argyrios and Goodall, Roger (2011) Simulation-based optimum sensor selection design for an uncertain EMS system via Monte-Carlo technique. In: 18th IFAC WC 2011, 28th August - 2nd September 2011, Università Cattolica del Sacro Cuore, Milano, Italy.

Full content URL: http://dx.doi.org/10.3182/20110828-6-IT-1002.01224

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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 loosing generality its efficacy is tested on an electromagnetic suspension system via appropriate realistic simulations.

Keywords:Industrial applications of optimal control, Evolutionary algorithms, Robust control applications, optimised sensor selection, modern control design, EMS systems, Monte Carlo, Genetic algorithms, bmjconvert
Subjects:H Engineering > H660 Control Systems
H Engineering > H100 General Engineering
G Mathematical and Computer Sciences > G990 Mathematical and Computing Sciences not elsewhere classified
H Engineering > H332 Rail Vehicle Engineering
Divisions:College of Science > School of Engineering
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ID Code:15821
Deposited On:26 Oct 2014 13:44

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