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Title: Optimised sensor selection for control and fault tolerance of electromagnetic suspension systems: a robust loop shaping approach
Authors: Michail, Konstantinos
Zolotas, Argyrios C.
Goodall, Roger M.
Issue Date: 2014
Publisher: Elsevier (© ISA)
Citation: MICHAIL, K., ZOLOTAS, A. and GOODALL, R., 2014. Optimised sensor selection for control and fault tolerance of electromagnetic suspension systems: a robust loop shaping approach. ISA Transactions, 53 (1), pp.97-109.
Abstract: This paper presents a systematic design framework for selecting the sensors in an optimised manner, simultaneously satisfying a set of given complex system control requirements, i.e. optimum and robust performance as well as fault tolerant control for high integrity systems. It is worth noting that optimum sensor selection in control system design is often a non-trivial task. Among all candidate sensor sets, the algorithm explores and separately optimises system performance with all the feasible sensor sets in order to identify fallback options under single or multiple sensor faults. The proposed approach combines modern robust control design, fault tolerant control, multiobjective optimisation and Monte Carlo techniques. Without loss of generality, it's efficacy is tested on an electromagnetic suspension system via appropriate realistic simulations.
Description: This paper was accepted for publication in the journal ISA Transactions and the definitive published version is available at https://doi.org/10.1016/j.isatra.2013.08.006
Sponsor: Parts of this research were supported by Engineering and Physical Sciences Research Council in United Kingdom, BAE Systems (Systems Engineering Innovation Center) under project grand ref. EP/D063965/1 and by NEW-ACE EPSRC network under project grand ref. EP/E055877/1.
Version: Accepted for publication
DOI: 10.1016/j.isatra.2013.08.006
URI: https://dspace.lboro.ac.uk/2134/27063
Publisher Link: https://doi.org/10.1016/j.isatra.2013.08.006
ISSN: 0019-0578
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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