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Modeling and Control of Multivariable Process Using Intelligent Techniques

Sensors & Transducers. 2010;121(10):68-76

 

Journal Homepage

Journal Title: Sensors & Transducers

ISSN: 2306-8515 (Print); 1726-5479 (Online)

Publisher: IFSA Publishing, S.L.

Society/Institution: International Frequency Sensor Association (IFSA)

LCC Subject Category: Technology: Technology (General)

Country of publisher: Spain

Language of fulltext: English

Full-text formats available: PDF

 

AUTHORS


Subathra Balasubramanian (Department of Chemical Engineering, National Institute of Technology, Tiruchirappalli-620015, Tamil Nadu, India)

Radhakrishnan T. K. (Department of Chemical Engineering, National Institute of Technology, Tiruchirappalli-620015, Tamil Nadu, India)

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 5 weeks

 

Abstract | Full Text

For nonlinear dynamic systems, the first principles based modeling and control is difficult to implement. In this study, a fuzzy controller and recurrent fuzzy controller are developed for MIMO process. Fuzzy logic controller is a model free controller designed based on the knowledge about the process. In fuzzy controller there are two types of rule-based fuzzy models are available: one the linguistic (Mamdani) model and the other is Takagiā€“Sugeno model. Of these two, Takagi-Sugeno model (TS) has attracted most attention. The fuzzy controller application is limited to static processes due to their feedforward structure. But, most of the real-time processes are dynamic and they require the history of input/output data. In order to store the past values a memory unit is needed, which is introduced by the recurrent structure. The proposed recurrent fuzzy structure is used to develop a controller for the two tank heating process. Both controllers are designed and implemented in a real time environment and their performance is compared.