Nonlinear model predictive control based on T-S fuzzy model for a PWR nuclear power plant

2014 ◽  
Author(s):  
Mengyue Wang ◽  
X. J. Liu
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Nuclear Power ◽  
Fuzzy Model ◽  
Nonlinear Model Predictive Control

scholarly journals Nonlinear Fuzzy Model Predictive Control for a PWR Nuclear Power Plant

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xiangjie Liu ◽  
Mengyue Wang
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Nuclear Power ◽  
High Efficiency ◽  
Fuzzy Model ◽  
Nonlinear Constraint ◽  
Pressurized Water ◽  
Plant Safety

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.

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