Genetic Algorithm Tuned Fuzzy Neural
Network for Non-linear System Control
T.K. Radhakrishnan1) and Madhubala T. Kadavarayar2)
1)Department of Chemical Engineering,
National Institute of Technology, Tiruchirappalli 620 015, INDIA.
e-mail: radha@nitt.edu
2) Department of Physics,National
Institute of Technology, Tiruchirappalli 620 015, INDIA. e-mail:
madhu_tk@rediffmail.com
Abstract
A fuzzy neural network controller is
designed for a non-linear process. In this investigation, a real-time control
of a conical liquid level system, which is a non-linear process, is studied.
A conical tank is highly non-linear since the cross section of the tank
varies with height. Here, the controller is tuned using genetic algorithms.
Genetic algorithms are used to tune the membership functions of the input
variables. The values of the parameters are constrained while running the
genetic algorithms in order to get better results. The performance of the
fuzzy neural network is compared to that of a well tuned PI controller.
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