KALMAN FILTER APPLICATION FOR DISTRIBUTED-PARAMETER ESTIMATION IN-REACTOR SYSTEMS

An application of the Kalman filter has been developed for the real-ti me identification of a distributed parameter in a nuclear power plant. This technique can be used to improve numerical method-based best-est imate simulation of complex systems such as nuclear power plants. The application to a reactor system involves a unique modal model that app roximates physical components, such as the reactor, as a coupled oscil lator, i.e., a modal model with coupled modes. In this model both stat es and parameters are described by an orthogonal expansion. The Kalman filter with the sequential least-squares parameter estimation algorit hm was used to estimate the modal coefficients of all states and one p arameter. Results show that this state feedback algorithm is an effect ive way to parametrically identify a distributed parameter system in t he presence of uncertainties.