Optimized adaptive neuro-fuzzy inference system for pH control

Author

Singh, Praveen Kumar ; Bhanot, Surekha ; Mohanta, H.K.

Author_Institution

Dept. of Electron. & Instrum., BITS Pilani, Pilani, India

fYear

2013

fDate

21-23 Sept. 2013

Firstpage

1

Lastpage

5

Abstract

pH control plays an important role in many modern industrial plants due to strict environment regulations. This paper presents fuzzy logic based pH control scheme for neutralization process in which genetic algorithm is used to optimize the various membership functions of fuzzy inference system. Further, using this optimized fuzzy inference system, adaptive neuro-fuzzy inference system for pH neutralization process is developed. Performances of both control schemes are compared for servo and regulatory operations. Results indicate that adaptive neuro-fuzzy inference system based control uses fewer rules as compared to optimized fuzzy logic based control.

Keywords

adaptive control; fuzzy logic; fuzzy reasoning; genetic algorithms; industrial plants; pH control; process control; production engineering computing; adaptive neuro-fuzzy inference system; fuzzy logic; genetic algorithm; industrial plants; membership functions; pH control scheme; pH neutralization process; regulatory operation; servo operation; adaptive neuro-fuzzy inference system; fuzzy control; genetic algorithm; optimization; pH neutralization process;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Electronic Systems (ICAES), 2013 International Conference on

Conference_Location

Pilani

Print_ISBN

978-1-4799-1439-5

Type

conf

DOI

10.1109/ICAES.2013.6659349

Filename

6659349