Universiti Teknologi Malaysia Institutional Repository

Recursive least square and fuzzy modeling using genetic algorithm for process control application

Abdul Rahman, Ribhan Zafira and Yusof, Rubiyah and Khalid, Marzuki (2007) Recursive least square and fuzzy modeling using genetic algorithm for process control application. In: First Asia International Conference on Modeling & Simulation(AMS 2007), 2007, Prince of Songkla University .

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Official URL: http://ieeexplore.ieee.org/document/4148692/

Abstract

A technique for the modelling of nonlinear process control using recursive least square and Takagi-Sugeno fuzzy system with genetic algorithm topology is described. This paper discusses the identification of parameters of the fuzzy sets at the antecedent part and linear model at the consequent part of fuzzy model within an application to process control. The key issues of finding the best model of the process are described. Results show that fuzzy model with genetic algorithm gives minimum mean squared error compare with recursive least square.

Item Type:Conference or Workshop Item (Paper)
Additional Information:First Asia International Conference on Modeling & Simulation(AMS 2007), Phuket, Thailand
Uncontrolled Keywords:recursive, genetic algorithm
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:14384
Deposited By: Mrs Liza Porijo
Deposited On:24 Aug 2011 07:16
Last Modified:20 Jun 2017 06:57

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