Abstracto

Efficient Hybrid Control of Shell and Tube Heat Exchanger Using Interval Type-2 and Adaptive Neuro Fuzzy Based Fuzzy Inference System

Borkar Pravin Kumar, Agrawal G.K, Qureshi M.F, Jha Manoj

In this paper, adaptive network based fuzzy inference system (ANFIS) was used in control applications of a Shell and Tube 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 Shell and Tube 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 paper deals with the design and application of an IT2 FLC+ANFIS controller for a Shell and Tube heat exchanger. 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 promises 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 proves its simplicity and superiority over the conventional PID controller.