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