Simulation-Based Optimum Sensor Selection Design for an Uncertain EMS System Via Monte-Carlo Technique

Konstantinos, Michail, Zolotas, A.C. and Goodall, Roger M. (2011) Simulation-Based Optimum Sensor Selection Design for an Uncertain EMS System Via Monte-Carlo Technique. In: 18th IFAC World Congress, 28th August - 2nd September 2011, Milan, Italy.

PDF - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (433kB)

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.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	T Technology > TF Railroad engineering and operation
Schools:	School of Computing and Engineering
Depositing User:	Cherry Edmunds
Date Deposited:	07 Jun 2013 13:42
Last Modified:	06 Dec 2016 20:20
URI:	http://eprints.hud.ac.uk/id/eprint/17749

Downloads

Repository Staff Only: item control page

View Item