A Takagi-Sugeno fuzzy model of a concentric-tubes heat exchanger

In the present study we develop a Takagi-Sugeno (TS) fuzzy model of a concentric-tubes heat exchanger. The model is structured on fuzzy logic reasoning with sets of linguistic rules describing the dynamic characteristics of the thermal system. Using a system identification technique based on adaptive neural networks, the fuzzy rules are derived from experimental data of the flow rates and fluid temperatures in the heat exchanger. The accuracy of the resulting model is assessed by predicting the time-dependent response of the outlet hot- and cold-water temperatures under a step-change in the mass flow rate of the cold fluid. The results indicate that the TS fuzzy model is able to estimate the behavior of the physical system with very little predicting errors. Upon the basis of this empirical model, in the near future we will report on a control strategy for the regulation and tracking of the outlet temperatures in the heat exchanger. Copyright © 2008 by ASME.

Adaptive neural networks; Cold fluid; Control strategies; Dynamic characteristics; Empirical model; Experimental data; Fluid temperatures; Fuzzy logic reasoning; Linguistic rules; Mass flow rate; Outlet temperature; Physical systems; System identification techniques; T-S fuzzy models; Takagi-sugeno fuzzy models; Thermal systems; Time-dependent response; Water temperatures; Flow rate; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Heat exchangers; Mechanical engineering; Mathematical models

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