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Design of dynamic neural observers

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2 Author(s)
Ahmed, M.S. ; Daimler-Benz AG, Ulm, Germany ; Riyaz, S.H.

A design of a nonlinear dynamic observer is proposed for determining the states of a nonlinear system. The design method uses a multi-layered feedforward neural network (MFNN) to approximate the nonlinear Kalman gain. Two different criteria are proposed for the network training. The training is based on a gradient descent algorithm that uses block partial derivatives. Simulation results on Van der Pol's equation and the classical inverted pendulum model are presented to validate the usefulness of the scheme

Published in:

Control Theory and Applications, IEE Proceedings -  (Volume:147 ,  Issue: 3 )