alexa Intelligent Optimal Control of a Heat Exchanger Using ANFIS and Interval Type-2 Based Fuzzy Inference System
ISSN ONLINE(2319-8753)PRINT(2347-6710)

International Journal of Innovative Research in Science, Engineering and Technology
Open Access

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Research Article

Intelligent Optimal Control of a Heat Exchanger Using ANFIS and Interval Type-2 Based Fuzzy Inference System

1Borkar Pravin Kumar, 2Jha Manoj, 3Qureshi M.F., 4Agrawal G.K.
  1. Department of Mechanical Engg., Rungta College of Engg. & Tech., Raipur, India
  2. Department of Applied Mathematics, RSR Rungta College of Engg. & Tech., India.
  3. Department of Electrical Engg., Govt. Polytechnic Narayanpur, India,
  4. Department of Mechanical Engg., Govt. Engg. College, Bilaspur, India.
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Abstract

In this paper, adaptive network based fuzzy inference system (ANFIS) was used in control applications of a Heat Exchanger as interval type-2 fuzzy logic controller (IT-2FL). Two adaptive networks based fuzzy inference systems were chosen to design type-2 fuzzy logic controllers for each control applications. The whole integrated system for control of Heat Exchanger is called IT2 FLC+ANFIS controller. Membership functions in interval type-2 fuzzy logic controllers were set as an area called footprint of uncertainty (FOU), which is limited by two membership functions of adaptive network based fuzzy inference systems; they were upper membership function (UMF) and lower membership function (LMF). This work deals with the design and application of an IT2 FLC+ANFIS controller for a heat exchanger. To deal with the problem of parameter adjustment, efficient neuro-fuzzy scheme known as the ANFIS (Adaptive Network-based Fuzzy Inference System) can be used. The IT2 FLC+ANFIS controller of the heat exchanger is compared with classical PID control. System behaviors were defined by Lagrange formulation and MATLAB computer simulations. The simulation results confirm that interval type2 fuzzy is one of the possibilities for successful control of heat exchangers. The advantage of this approach is that it is not a linear-model-based strategy. Comparison of the simulation results obtained using IT2 FLC+ANFIS controller and those obtained using classical PID control demonstrates the effectiveness and superiority of the proposed approach because of the smaller consumption of the heating medium

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