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An adaptive extended Kalman filter using artificial neural networks

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3 Author(s)
Stubberud, S.C. ; Orincon Corp., San Diego, CA, USA ; Lobbia, R.N. ; Owen, M.

Develops an adaptive state-estimation technique using artificial neural networks, referred to as a neuro-observer. The neuro-observer is an extended Kalman filter structure that has its state-coupling function augmented by an artificial neural network that captures the unmodeled dynamics. The neural network of the neuro-observer trains on-line using an extended Kalman filter training paradigm. Improvement in the system model then provides for a more accurate state estimate in the feedback loop, thus enhancing the control signal so that the system behaves in a closer to optimal fashion

Published in:
Decision and Control, 1995., Proceedings of the 34th IEEE Conference on  (Volume:2 )

Date of Conference: 13-15 Dec 1995

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