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

Full text not available from this repository

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
~Pre-2010 Faculty Structure > Environment and Technology > Bristol Institute of Technology
~Pre-2012 Faculty Structure > Faculty of Environment and Technology
ID Code:5909
Deposited By: R. Upload account
Deposited On:22 Jan 2010 15:10
Last Modified:14 Mar 2013 15:31

Repository Staff Only: item control page
Copyright 2013 © UWE better together