A neural network enhanced generalised minimum variance self tuning PID control algorithm for complex dynamic systems

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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

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Publisher's URL: http://pii.sagepub.com/content/216/3/265.abstract

Item Type:	Article
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.
Uncontrolled Keywords:	neuro PID controller, complex dynamic plants, self-tuning control
Faculty/Department:	Faculty of Environment and Technology
ID Code:	5909
Deposited By:	R. Upload account
Deposited On:	22 Jan 2010 15:10
Last Modified:	12 Aug 2013 07:58

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A neural network enhanced generalised minimum variance self tuning PID control algorithm for complex dynamic systems

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