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In this paper, a fuzzy model predictive control method is applied to design an automatic controller for thermal power control in pressurized water reactors. The future reactor power is predicted by using the fuzzy model identified by a subtractive clustering method of a fast and robust algorithm. The objectives of the proposed fuzzy model predictive controller are to minimize both the difference between the predicted reactor power and the desired one, and the variation of the control rod positions. Also, the objectives are subject to maximum and minimum control rod positions and maximum control rod speed. The genetic algorithm that is useful to accomplish multiple objectives is used to optimize the fuzzy model predictive controller. A three-dimensional nuclear reactor analysis code is used to verify the proposed controller for a nuclear reactor. From results of numerical simulation to check the performance of the proposed controller at the 5%/min ramp increase or decrease of a desired load and its 10% step increase or decrease which are design requirements, it was found that the nuclear power level controlled by the proposed fuzzy model predictive controller could track the desired power level very well.
Na et al. (Thu,) studied this question.