A neural network enhanced generalised minimum variance self tuning PID control algorithm for complex dynamic systems
Zhu, Q. and Warwick, K.
(2002)
A neural network enhanced generalised minimum variance self tuning PID control algorithm for complex dynamic systems.
Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 216 (3).
pp. 265-273.
ISSN 0959-6518
Available from: http://eprints.uwe.ac.uk/5909
Full text not available from this repository Publisher's URL: http://pii.sagepub.com/content/216/3/265.abstract | Item Type: | Article |
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| Additional Information: | This work represents a fundamental concept development in neural network enhanced control system design. Particularly the significant step of simplification of design of PID controllers for nonlinear dynamic plants. |
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| Uncontrolled Keywords: | neuro PID controller, complex dynamic plants, self-tuning control |
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| Faculty/Department: | Faculty of Environment and Technology |
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| ID Code: | 5909 |
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| Deposited By: |
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| Deposited On: | 22 Jan 2010 15:10 |
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| Last Modified: | 14 Feb 2017 12:33 |
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