Performance Improvement of Fuzzy Logic Controller Using Neural Network. (2016)

• Record Type: Journal Article
• Authors: Rajan, Susmitha; Sahadev, Saurabh
• Is Part Of: Procedia technology. Volume 24(2016)
• Page Start: 704
• Page End: 714
• Publication Date: 2016
• Subjects: Fuzzy logic -- Neural Network -- Coupled Tank System; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.05.197
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: Classical control theory is based on the mathematical models of the physical plants. Getting an accurate model of the plant is a basic problem in designing controllers in process industries. The problems of classical control schemes can be solved by incorporating the artificial intelligence. The aim of this paper is to present a versatile technique, Fuzzy Logic which is simple and easy to understand. But the Fuzzy frame work is not formalized. An expert's knowledge is needed for the accurate tuning of Fuzzy Logic controller. This paper presents a method for tuning Fuzzy Logic controller. Tuning can be effectively done by using Neural network. In this research an attempt has been made to design a Fuzzy Logic controller for a coupled tank system, using neural network as a tuning tool. The simulation and real time responses shows the effectiveness of the proposed scheme.