Due to nonlinear dynamic characteristics relationship between the R rod position and coolant average temperature in nuclear reaction core

the current fixed load control system of nuclear power plant has difficulties in making the nuclear power in reactor core trace the unit load variation rapidly.Against this problem

a nonparametric model set of dynamic characteristic relationships between the R rod position and coolant average temperature were established.On the basis of the dynamic matrix predictive control algorithm

the model controller was designed.Moreover

using the MATLAB/SIMULINK

the multi-model dynamic matrix predictive control system for coolant average temperature was built up and then connected to the simulation model for nuclear power station to form the simulation platform.In high power operation state

by using the simulation model data in nuclear power plants

the multi-model dynamic matrix predictive controller and the conventional PI controller were compared to verify the effectiveness and superiority of the designed multi-model dynamic matrix predictive controller.The evaluation indexes of tracing effect of coolant average temperature within 2 000 sand the simulation results show that

the tracing effect of this multi-model dynamic matrix predictive controller is dramatically better than that of the conventional PI controller during unit load ascension and descending process.