Development of genetic algorithm-based fuzzy logic controller for conical tank process. (1st January 2013)

• Record Type: Journal Article
• Authors: Arivalahan, R.; Subbaraj, P.; Devaraj, D.
• Is Part Of: International journal of industrial and systems engineering. Volume 13:Number 4(2013)
• Page Start: 442
• Page End: 461
• Publication Date: 2013-01-01
• Subjects: non-linear conical tank process -- adaptive proportional integral controller -- genetic algorithm-based fuzzy logic controller -- integral square error; Systems engineering -- Periodicals; Industrial engineering -- Periodicals; 620.001171
• Languages: English
• ISSNs: 1748-5037

Abstract

The proportional integral derivative controllers are widely used in industries for controlling the different process variables due to its simplicity, flexibility and efficiency. Recently, the control of non-linear processes in the industries have turned the attention towards the intelligent controllers such as neural networks, fuzzy logic controller (FLC), genetic algorithm-(GA) tuned controllers, adaptive controller, predictive controller, robust controller, etc. This work focuses on developing a GA-based FLC for conical tank. A conical tank is a highly non-linear process due to the variation in the area of cross section of the level system with change in shape. Conventionally, a parameter adaptive proportional integral (PI) controller has been designed for non-linear process. Alternatively, in this work, an intelligent controller (GA-based FLC) is designed for the control of non-linear process to ensure the exact level control. The experimental results are obtained for servo and regulatory response of the process. The GA-based FLC is compared with adaptive PI controller.