Sliding Model Observer Based On-line Estimation of Precursor Density for Pressurized Water Reactor

Precursor density is one of the key state parameters of nuclear reactor, and is very important parameter to safety control of reactor, but it cannot be measured directly. An improved precursor density estimation algorithm was proposed based on uniform second order sliding model observer, which introduced a correction term according relationship of precursor density estimated error and second order state estimated error. The proposed algorithm was tested on a SIMULINK based lamped model of pressurized water reactor. Simulation results show that the algorithm has high accuracy, satisfactory convergence, strong noise resistance and acceptable robustness under parametric perturbations.