This paper presents a new methodology of designing of non-linear dynamic neural model in the state-space representation. Furthermore, an application of the Unscented Kalman Filter to the training of the designed neural model is also shown. The final part of this work provides an illustrative example of the application of the proposed methodology to the identification and robust fault detection of the tunnel furnace.