In a nuclear power plant, the water level of the U-tube steam generator (UTSG) must be maintained within a safe range. Traditional control methods encounter difficulties due to the complexity, strong nonlinearity and “swell and shrink” effects, especially at low power levels. A properly designed robust model predictive control can well solve this problem. In this paper, a quasi-min-max fuzzy model predictive controller is developed for controlling the constrained UTSG system. While the online computational burden could be quite large for the real-time control, a bank of ellipsoid invariant sets together with the corresponding feedback control laws are obtained by off-line solving linear matrix inequalities (LMIs). Based on the UTSG states, the online optimization is simplified as a constrained optimization problem with a bisection search for the corresponding ellipsoid invariant set. Simulation results are given to show the effectiveness of the proposed controller.
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Liu et al. (2015) studied this question.
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