Neural networks for linear control: An analysis

Kevin Warwick

Mathematics and Computers in Simulation (MATCOM), 1996, vol. 41, issue 1, 29-37

Abstract: This paper considers the use of radial basis function and multi-layer perceptron networks for linear or linearizable, adaptive feedback control schemes in a discrete-time environment. A close look is taken at the model structure selected and the extent of the resulting parameterization. A comparison is made with standard, nonneural network algorithms, e.g. self-tuning control.

Date: 1996
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:41:y:1996:i:1:p:29-37

DOI: 10.1016/0378-4754(95)00056-9

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