Sharma, S.K. Sharma and McLoone, Sean F. and Irwin, G.W. (2005) Genetic algorithms for local controller network construction. IEE Proceedings on Control Theory and Applications, 152 (5). pp. 587-597.

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Abstract

Local Controller Networks (LCNs) provide nonlinear control by interpolating between a set of locally valid, subcontrollers covering the operating range of the plant. Constructing such networks typically requires knowledge of valid local models. This paper describes a new genetic learning approach to the construction of LCNs directly from the dynamic equations of the plant, or from modelling data. The advantage is that a priori knowledge about valid local models is not needed. In addition to allowing simultaneous optimisation of both the controller and validation function parameters, the approach aids transparency by ensuring that each local controller acts independently of the rest at its operating point. It thus is valuable for simultaneous design of the LCNs and identification of the operating regimes of an unknown plant. Application results from a highly nonlinear pH neutralisation process and its associated neural network representation are utilised to illustrate these issues.

Item Type:	Article
Additional Information:	This paper is a postprint of a paper submitted to and accepted for publicatin in (journal/conference) and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library
Keywords:	Local Controller Networks
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering
Item ID:	686
Depositing User:	Sean McLoone
Date Deposited:	23 Aug 2007
Journal or Publication Title:	IEE Proceedings on Control Theory and Applications
Publisher:	Institution of Engineering and Technology
Refereed:	Yes
URI:	http://www.theiet.org/publications/
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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