An application of the Kalman filter has been developed for the real-time identification of a distributed parameter in a nuclear power plant. This technique can be used to improve numerical method-based best-estimate simulation of complex systems such as nuclear power plants. The application to a reactor system involves a unique modal model that approximates physical components, such as the reactor, as a coupled oscillator, i.e., a modal model with coupled modes. In this model both states and parameters are described by an orthogonal expansion. The Kalman filter with the sequential least-squares parameter estimation algorithm was used to estimate the modal coefficients of all states and one parameter. Results show that this state feedback algorithm is an effective way to parametrically identify a distributed parameter system in the presence of uncertainties.