Nonlinear Fuzzy Model Predictive Control for a PWR Nuclear Power Plant

Xiangjie Liu and Mengyue Wang

Mathematical Problems in Engineering, 2014, vol. 2014, 1-10

Abstract:

Reliable power and temperature control in pressurized water reactor (PWR) nuclear power plant is necessary to guarantee high efficiency and plant safety. Since the nuclear plants are quite nonlinear, the paper presents nonlinear fuzzy model predictive control (MPC), by incorporating the realistic constraints, to realize the plant optimization. T-S fuzzy modeling on nuclear power plant is utilized to approximate the nonlinear plant, based on which the nonlinear MPC controller is devised via parallel distributed compensation (PDC) scheme in order to solve the nonlinear constraint optimization problem. Improved performance compared to the traditional PID controller for a TMI-type PWR is obtained in the simulation.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:908526

DOI: 10.1155/2014/908526

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