Gas turbine engine controller design using multiobjective genetic algorithms
Gas turbine engine controller design using multiobjective genetic algorithms
This paper describes the use of multiobjective genetic algorithms (MOGAs) in the design of a multivariable control system for a gas turbine engine. It is shown how the MOGA confers an immediate advantage over conventional multiobjective optimization methods by evolving a family of Pareto-optimal solutions allowing the control engineer to examine the trade-offs between the different design objectives. In addition, the paper demonstrates how the genetic algorithm can be used to search in both controller structure and parameter space thereby offering a potentially more general approach to optimization in controller design than traditional numerical methods.
214-219
Chipperfield, A.
524269cd-5f30-4356-92d4-891c14c09340
Fleming, P.
ea45da65-8bd1-42cf-9c43-023aac2b3921
14 September 1995
Chipperfield, A.
524269cd-5f30-4356-92d4-891c14c09340
Fleming, P.
ea45da65-8bd1-42cf-9c43-023aac2b3921
Chipperfield, A. and Fleming, P.
(1995)
Gas turbine engine controller design using multiobjective genetic algorithms.
In IEE Conference Publication.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper describes the use of multiobjective genetic algorithms (MOGAs) in the design of a multivariable control system for a gas turbine engine. It is shown how the MOGA confers an immediate advantage over conventional multiobjective optimization methods by evolving a family of Pareto-optimal solutions allowing the control engineer to examine the trade-offs between the different design objectives. In addition, the paper demonstrates how the genetic algorithm can be used to search in both controller structure and parameter space thereby offering a potentially more general approach to optimization in controller design than traditional numerical methods.
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Published date: 14 September 1995
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Local EPrints ID: 470252
URI: http://eprints.soton.ac.uk/id/eprint/470252
PURE UUID: 30a925f6-e4ff-4fca-ad85-d9da0a7c92dd
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Date deposited: 05 Oct 2022 16:34
Last modified: 23 Feb 2023 02:45
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Author:
P. Fleming
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