Controlling a system using an artifical neural network and artificial neural network training

Abstract

Apparatus and method of training an artificial neural network, NN, useable as a controller for a system comprises obtaining (402) input data representing a tapped delay line comprising a plurality of reference signals of the system and inputting (404) the reference signals to a respective plurality of NNs that output a respective plurality of control signals. The plurality of NNs comprise a first NN and at least one further NN and weights and biases of the at least one further NN correspond to weights and biases of a current iteration of the first NN. The control signals are provided (406) to a model that simulates the system and outputs a model signal. A system error signal is generated (408) using the model signal, and a next iteration of the plurality of NNs is trained (410) using training data comprising the obtained input data and the system error signal.

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Identifiers

ORCID for Jordan Cheer: orcid.org/0000-0002-0552-5506

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