A new neural state observer for non linear plants is proposed. Using a dynamical backpropagation learning algorithm, a non linear dynamical system, the neural observer, is built in order to reproduce the input/output behaviour of an unknown non linear plant and to give us an estimation by the output of the plant state. A straightforward example illustrates the proposed technique. Simulation results seem to be attractive.

Adaptive neural state observer for unknown nonlinear plants

BICCHI, ANTONIO;LANDI, ALBERTO;
1992

Abstract

A new neural state observer for non linear plants is proposed. Using a dynamical backpropagation learning algorithm, a non linear dynamical system, the neural observer, is built in order to reproduce the input/output behaviour of an unknown non linear plant and to give us an estimation by the output of the plant state. A straightforward example illustrates the proposed technique. Simulation results seem to be attractive.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/18959
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