Title: Design of cluster-wise optimal fuzzy logic controllers to model input-output relationships of some manufacturing processes
Authors: Tushar, Dilip Kumar Pratihar
Addresses: Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur, Kharagpur-721 302, India. ' Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur, Kharagpur-721 302, India
Abstract: In the present study, fuzzy logic (FL)-based approaches have been developed to determine the input-output relationships of some manufacturing processes, which may be non-linear in nature. Moreover, the degree of non-linearity may not be the same over the entire range of the variables. The input-output space has been clustered based on the similarity of the data points and cluster-wise linear regressions have been carried out. Takagi and Sugeno|s approach of fuzzy logic controller (FLC) has been implemented cluster-wise using the pre-determined regression equations. A genetic algorithm (GA) has been utilised to optimise both cluster-properties as well as knowledge base of the FLCs developed based on two types of clustering algorithm, namely entropy-based approach and fuzzy C-means algorithm. The performances of above two FLCs have been compared in the present work.
Keywords: fuzzy logic controllers; FLC; clustering methods; entropy; genetic algorithms; GAs; manufacturing process; fuzzy control; input-output relationships; optimisation.
International Journal of Data Mining, Modelling and Management, 2009 Vol.1 No.2, pp.178 - 205
Published online: 26 May 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article