Improved MOGA-tuning and visualization for a hybrid control system
Improved MOGA-tuning and visualization for a hybrid control system
A hybrid controller is developed for a solar-thermal power plant using a gain-scheduled controller with feedforward to control the more linear operating regimes and a fuzzy PI incremental controller for the highly nonlinear operating region of the plant. An enhanced method of MOGA-tuning is employed by first optimizing the number of input/output membership functions using neuro-fuzzy data clustering. Enhancements to the visualization properties of the MOGA's graphical user interface are evaluated to improve the decision maker's choice when deciding between non-dominated solutions or potential fuzzy controller inference systems.
solar thermal power plant, multiobjective genetic algorithm (MOGA), gain schedule control, fuzzy logic control, adaptive neuro-fuzzy inference system, evolving trade-off
Stirrup, R.
79047437-1b34-4335-bb5d-d48e15e4c03e
Chipperfield, A.J.
524269cd-5f30-4356-92d4-891c14c09340
2005
Stirrup, R.
79047437-1b34-4335-bb5d-d48e15e4c03e
Chipperfield, A.J.
524269cd-5f30-4356-92d4-891c14c09340
Stirrup, R. and Chipperfield, A.J.
(2005)
Improved MOGA-tuning and visualization for a hybrid control system.
IFAC Proceedings Volumes, 16 (1).
(doi:10.3182/20050703-6-CZ-1902.00870).
Abstract
A hybrid controller is developed for a solar-thermal power plant using a gain-scheduled controller with feedforward to control the more linear operating regimes and a fuzzy PI incremental controller for the highly nonlinear operating region of the plant. An enhanced method of MOGA-tuning is employed by first optimizing the number of input/output membership functions using neuro-fuzzy data clustering. Enhancements to the visualization properties of the MOGA's graphical user interface are evaluated to improve the decision maker's choice when deciding between non-dominated solutions or potential fuzzy controller inference systems.
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IFAC-05-2906-Final.pdf
- Author's Original
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Published date: 2005
Keywords:
solar thermal power plant, multiobjective genetic algorithm (MOGA), gain schedule control, fuzzy logic control, adaptive neuro-fuzzy inference system, evolving trade-off
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Local EPrints ID: 58757
URI: http://eprints.soton.ac.uk/id/eprint/58757
ISSN: 1474-6670
PURE UUID: 84655aa7-78e2-43f4-884e-3761a05ee643
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Date deposited: 18 Aug 2008
Last modified: 16 Mar 2024 03:31
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Author:
R. Stirrup
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