Development of genetic algorithm-based fuzzy logic controller for conical tank process
by R. Arivalahan; P. Subbaraj; D. Devaraj
International Journal of Industrial and Systems Engineering (IJISE), Vol. 13, No. 4, 2013

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.

Online publication date: Fri, 27-Dec-2013

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