Adaptive Control of CSTR Using Feedback Linearization Based on Grey-Box Modeling

Author

Hourfar, Farzad ; Salahshoo, Karim

Author_Institution

Univ. of Tehran, Tehran

fYear

2008

fDate

6-8 April 2008

Firstpage

7

Lastpage

12

Abstract

In this paper, a new technique for adaptive control of nonlinear chemical processes based on feedback linearization method is presented. The method is based on semi-mechanistic or grey-box modeling. By this method, only the difficult-to-model part or complicated part of the plant is identified by an adaptive neural network and the remaining parts of the system are obtained online by using first-principle model of the process and special measuring techniques. The method is applied to a well-known CSTR benchmark process and its advantages and drawbacks are discussed.

Keywords

adaptive control; chemical reactors; neural nets; CSTR benchmark process; adaptive control; adaptive neural network; feedback linearization method; first-principle model; grey-box modeling; nonlinear chemical process; Adaptive control; Chemical processes; Continuous-stirred tank reactor; Control nonlinearities; Control systems; Neurofeedback; Nonlinear control systems; Petroleum; State feedback; Uncertainty; Adaptive Control; CSTR; GLC; Grey-Box modeling;

fLanguage

English

Publisher

ieee

Conference_Titel

Networking, Sensing and Control, 2008. ICNSC 2008. IEEE International Conference on

Conference_Location

Sanya

Print_ISBN

978-1-4244-1685-1

Electronic_ISBN

978-1-4244-1686-8

Type

conf

DOI

10.1109/ICNSC.2008.4525173

Filename

4525173