Neural network predictive control of a heat exchanger
نویسندگان
چکیده
Possibility to use a neural network predictive control (NNPC) strategy for control of a heat exchanger is studied. The heat exchanger is a tubular one and it is used for preheating of petroleum by hot water. The control objective is to keep the output temperature of the heated stream at a desired value and minimize the energy consumption. The advantage of the NNPC is that it is not a linear-model-based strategy and the control input constraints are directly included into the synthesis. The NNPC of the heat exchanger is compared with classical PID control by simulations experiments. Comparison of the simulation results obtained using NNPC and those obtained by classical PID control demonstrates the effectiveness and superiority of the NNPC because of smaller consumption of heating medium.
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