posted on 2017-10-23, 15:11authored byKonstantinos Michail, Argyrios C. Zolotas, Roger Goodall
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.
Funding
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.
History
School
Mechanical, Electrical and Manufacturing Engineering
Published in
ISA Transactions
Volume
53
Issue
1
Pages
97 - 109
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.
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
Publication date
2014
Notes
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