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Online tuning of fuzzy logic controller using Kalman algorithm for conical tank system
ARTICLE

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Journal of Applied Research and Technology Volume 15, Number 5, ISSN 1665-6423 Publisher: Elsevier Ltd

Abstract

In a non-linear process like conical tank system, controlling the liquid level was carried out by proportional integral derivative (PID) controller. But then it does not provide an accurate result. So in order to obtain accurate and effective response, intelligence is added into the system by using fuzzy logic controller (FLC). FLC which helps in maintaining the liquid level in a conical tank has been developed and applied to various fields. The result acquired using FLC will be more precise when compared to PID controller. But FLC cannot adapt a wide range of working environments and also there is no systematic method to design the membership functions (MFs) for inputs and outputs of a fuzzy system. So an adaptive algorithm called Kalman algorithm which employs fuzzy logic rules is used to adapt the Kalman filter to accommodate changes in the system parameters. The Kalman algorithm which employs fuzzy logic rules adjust the controller parameters automatically during the operation process of a system and controller is used to reduce the error in noisy environments. This technique is applied in a conical tank system. Simulations and results show that this method is effective for using fuzzy controller.

Citation

Tamilselvan, G.M. & Aarthy, P. (2017). Online tuning of fuzzy logic controller using Kalman algorithm for conical tank system. Journal of Applied Research and Technology, 15(5), 492-503. Elsevier Ltd. Retrieved September 27, 2022 from .

This record was imported from Journal of Applied Research and Technology on January 29, 2019. Journal of Applied Research and Technology is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/j.jart.2017.05.004

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