DocumentCode :
2535555
Title :
Multiple-model control of pH neutralization plant using the SOM neural networks
Author :
Bashivan, Pouya ; Fatehi, Alireza ; Peymani, Ehsan
Author_Institution :
Dept. of Control Eng., K.N. Toosi Univ. of Technol., Tehran
Volume :
1
fYear :
2008
fDate :
11-13 Dec. 2008
Firstpage :
115
Lastpage :
119
Abstract :
A multiple-model adaptive controller is developed using the self-organizing map (SOM) neural network. The considered controller which we name it as multiple controller via SOM (MCSOM) is evaluated on the pH neutralization plant. An improved switching algorithm based on excitation level of plant has also been suggested for systems with noisy environments. Identification of pH plant using SOM is discussed and performance of the multiple-model controller is compared to the self tuning regulator (STR) controller.
Keywords :
adaptive control; chemical industry; neurocontrollers; pH control; pole assignment; process control; self-organising feature maps; time-varying systems; SOM neural network; excitation level; improved switching algorithm; multiple-model adaptive controller; noisy environment; pH neutralization plant; pole placement; self tuning regulator controller; self-organizing map; Adaptive control; Automatic control; Clustering algorithms; Estimation error; Mathematical model; Neural networks; Performance analysis; Programmable control; State feedback; Switches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
India Conference, 2008. INDICON 2008. Annual IEEE
Conference_Location :
Kanpur
Print_ISBN :
978-1-4244-3825-9
Electronic_ISBN :
978-1-4244-2747-5
Type :
conf
DOI :
10.1109/INDCON.2008.4768811
Filename :
4768811
Link To Document :
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