Advanced Control of Heat Exchangers in Series

The paper deals with the design and application of advanced control approaches assuming the considered controlled system is a cooling system of four heat exchangers in series. Neural network model-based predictive control (NNPC) strategy, feedback linearization control, and fuzzy PI control are chosen. The results of the proposed control strategies are studied and verified and then compared with the results obtained by a conventional PID controller and the gain scheduled PID controller. The results show that NNPC and fuzzy control can improve heat exchangers control and achieve objectives such as reducing cooling water consumption.

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