Fuzzy Model-based Neural Network Predictive Control of a Heat Exchanger
نویسندگان
چکیده
The paper investigates a predictive control algorithm to regulate the output petroleum temperature of the tubular heat exchanger. In the controller design, a Takagi–Sugeno fuzzy model is applied in combination with the model predictive control algorithm. The process model in form of the Takagi–Sugeno fuzzy model is obtained via subtractive clustering from the plant's data set. The neural network is used to predict the system outputs and trained on the fuzzy model by the Levenberg-Marquardt algorithm. The simulation results show that the proposed control strategy has good set-point tracking and adequate disturbance rejection ability.
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