Title: A genetic-based hybrid intelligent controller for looper tension in steel rolling mills

Authors: S. Thangavel, V. Palanisamy, K. Duraiswamy, S. Chenthur Pandian

Addresses: K.S.Rangasamy College of Technology, Tiruchengode 637 209, India. ' Government College of Technology, Coimbatore 641013, India. ' K.S.Rangasamy College of Technology, Tiruchengode 637 209, India. ' K.S.Rangasamy College of Technology, Tiruchengode 637 209, India

Abstract: Most industrial applications are non-linear. Fuzzy Logic Controller (FLC) is the most useful approach to achieve adaptiveness in the case of a non-linear system. Fuzzy logic control provides a systematic method of incorporating human expertise to a non-linear system. Neural networks are integrated with fuzzy logic which forms a neuro fuzzy system. A Genetic Algorithm (GA) is used to optimise membership functions of neuro fuzzy system to give optimal output and hence form the Hybrid Intelligent Controller (HIC). This paper demonstrates the effectiveness of HIC in optimising the looper height in steel rolling mills compared with conventional controllers, FLC. The simulation result depicts that HIC quickly restore the speed of the main drive and hence the looper height is quickly reduced to its optimal (zero) value which in turn ensures safe working condition in steel rolling mills.

Keywords: hot strip finishing mills; looper tension; conventional controllers; fuzzy logic controllers; FLCs; neuro-fuzzy control; genetic algorithms; GA; hybrid control; steel rolling mills; fuzzy control; intelligent control; neural networks.

DOI: 10.1504/IJMIC.2007.014939

International Journal of Modelling, Identification and Control, 2007 Vol.2 No.3, pp.219 - 228

Available online: 20 Aug 2007 *

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