Utilizing the real recorded data obtained from a power plant, nonlinear low order state space models are developed for an once-through type power plant boiler.
In order to understand the boiler dynamics and to use for designing back-up controllers, the unknown model parameters were estimated by means of a nonlinear estimation technique, i.e. the Extended Kalman Filter Method.
It is shown that simulation results coincide with the measurement data within 5% relative error range, which are acceptable from a back-up control point of view.
