TY - GEN
T1 - Estimation of the precursor power and internal reactivity in a nuclear reactor by a neural observer
AU - Humberto Pérez-Cruz, J.
AU - Poznyak, Alexander
PY - 2007
Y1 - 2007
N2 - This paper presents the design of a nonlinear robust observer for the estimation of the neutron precursor power and internal reactivity in a nuclear research reactor when only the input and the neutron power are available for measurement. The observer is based on a differential neural network with internal and external layers. Besides, this observer has two correction terms: Luenberger one and sliding mode one. This last term is intended to reduce the output external noise effect. The neural network is initially trained off-line using a very simplified third order nonlinear model of the nuclear reactor. The off-line training process is robust with respect to the model employed. Thus, when this preliminary training has finished, the neural observer can work as a completely physical model-free system and can carry out the on-line state estimation within a small margin of error despite uncertainty and noise. The efficiency of this technique with a guaranteed bound for the averaged estimation error is illustrated by simulation.
AB - This paper presents the design of a nonlinear robust observer for the estimation of the neutron precursor power and internal reactivity in a nuclear research reactor when only the input and the neutron power are available for measurement. The observer is based on a differential neural network with internal and external layers. Besides, this observer has two correction terms: Luenberger one and sliding mode one. This last term is intended to reduce the output external noise effect. The neural network is initially trained off-line using a very simplified third order nonlinear model of the nuclear reactor. The off-line training process is robust with respect to the model employed. Thus, when this preliminary training has finished, the neural observer can work as a completely physical model-free system and can carry out the on-line state estimation within a small margin of error despite uncertainty and noise. The efficiency of this technique with a guaranteed bound for the averaged estimation error is illustrated by simulation.
UR - http://www.scopus.com/inward/record.url?scp=49749094786&partnerID=8YFLogxK
U2 - 10.1109/ICEEE.2007.4345030
DO - 10.1109/ICEEE.2007.4345030
M3 - Contribución a la conferencia
AN - SCOPUS:49749094786
SN - 1424411661
SN - 9781424411665
T3 - 2007 4th International Conference on Electrical and Electronics Engineering, ICEEE 2007
SP - 310
EP - 313
BT - 2007 4th International Conference on Electrical and Electronics Engineering, ICEEE 2007
T2 - 2007 4th International Conference on Electrical and Electronics Engineering, ICEEE 2007
Y2 - 5 September 2007 through 7 September 2007
ER -