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Adaptive neuro-fuzzy interface system (ZNFIS) controller for polymerization reactor

conference contribution
posted on 2016-08-18, 00:00 authored by Anwar HosenAnwar Hosen, Saeid Nahavandi, L Sinnott, Abbas KhosraviAbbas Khosravi
It is a challenging task to control polymerization reactor due to the complex reactions mechanism. Moreover, the dynamic behaviour of the polymerization reactor is highly nonlinear. Thousand of reactions involed during polymerization that make the system complex in nature. Artificial intelligent appeared as promising tool to control such kind of nonlinear and complex processes. In the present work, a advanced nonlinear controller, namely adaptive neuro-fuzzy interface system (ANFIS) is proposed and designed for polymerization reactor. Sugeno type fuzzy interface system is used in ANFIS. Hybrid optimization algorithm, a combination of least-square estimation and backpropagation methods is used to optimize the neural network-based fuzzy output model. Styrene free radical polymerisation batch reactor is used as a case study. Simulation results demonstrated that the tracking performance of the ANFIS-based controller is better than the traditional neural network (NN)-based controller.

History

Event

Norbert Wiener in the 21st Century. Conference (2016 : Melbourne, Vic.)

Pagination

34 - 39

Publisher

IEEE

Location

Melbourne, Vic.

Place of publication

Piscataway, N.J.

Start date

2016-07-13

End date

2016-07-15

ISBN-13

9781467383806

Language

eng

Publication classification

E Conference publication; E1 Full written paper - refereed

Copyright notice

2016, IEEE

Title of proceedings

21CW 2016 : Proceedings of the IEEE Conference on Norbert Wiener in the 21st Century