DocumentCode :
3413978
Title :
Intelligent controller implementation in real time for a nonlinear process
Author :
Nithya, S. ; Gour, Abhay Singh ; Sivakumaran, N. ; Radhakrishnan, T.K. ; Balasubramanian, T. ; Anantharaman, N.
Author_Institution :
Sch. of Electr. & Electron. Eng., Shanmugha Arts Sci. Technol. Res. Acad., Thanjavur
fYear :
2008
fDate :
June 30 2008-July 2 2008
Firstpage :
2508
Lastpage :
2513
Abstract :
Chemical process presents many challenging control problems due to their non-linear dynamic behavior, uncertain and time varying parameters, constraints on manipulated variable, interaction between manipulated and controlled variables, unmeasured and frequent disturbances, dead time on input and measurements. Because of the inherent non-linearity, most of the chemical process industries are in need of traditional control techniques. The fluid level control problem is a common one associated with storage tanks, and blending and reaction vessels in the process industries. Control of liquid level in a spherical tank is non-linear due to the variation in the area of cross section of the level system with height. System identification of this non-linear process is done black box model, which is identified to be non-linear and approximated to be a First Order Plus Dead Time (FOPDT) model. Controllers, Proportional Integral (PI) controller using Skogestad (2003) tuning rule, Fuzzy Logic Controller (FLC) are developed for the control of liquid level in spherical tank. The real time control of the above said process is implemented in MATLAB using ADAMpsilas data acquisition module. The performance comparison of these controllers is compared to various performance indices. The real time implementation shows that the FLC produces improved control performance with respect to that of conventional PI controller.
Keywords :
data acquisition; fuzzy control; intelligent control; data acquisition system; first plus dead time; fuzzy logic controller; intelligent controller; nonlinear process; proportional integral; Chemical industry; Chemical processes; Fluid dynamics; Industrial control; Level control; Manipulator dynamics; Mathematical model; Pi control; Proportional control; Time measurement; Data Acquisition System; Fuzzy Logic PI Controller; Model Identification; Non Linear System;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics, 2008. ISIE 2008. IEEE International Symposium on
Conference_Location :
Cambridge
Print_ISBN :
978-1-4244-1665-3
Electronic_ISBN :
978-1-4244-1666-0
Type :
conf
DOI :
10.1109/ISIE.2008.4677239
Filename :
4677239
Link To Document :
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