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

A new approach for power and temperature control in pressurized water reactor (PWR) nuclear power plant using nonlinear model predictive control (MPC) based on T-S fuzzy model is presented. MPC is possibly the only advanced control scheme able to deal with constraints, namely, it can regulate and control system variables within the pre-defined ranges. Nevertheless, it is limited for its theoretical derivation based on linear models. T-S fuzzy modeling method is used for approximating the nonlinear system by local linear models, based on which the nonlinear MPC controller is devised via parallel distributed compensation (PDC) scheme in order to solve the nonlinearity and the constraint problems. The proposed controller presents much better performance than the conventional PID controller in the simulation.