Warwick, K. (1995) A critique of neural networks for discrete-time linear control. International Journal of Control, 61 (6). pp. 1253-1264. ISSN 0020-7179 doi: 10.1080/00207179508921955
Abstract/Summary
This paper discusses the use of 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 parametrization. A comparison is made with standard, non-perceptron algorithms, e.g. self-tuning control, and it is shown how gross over-parametrization can occur in the neural network case. Because of the resultant heavy computational burden and poor controller convergence, a strong case is made against the use of neural networks for discrete-time linear control.
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| Item Type | Article |
| URI | https://reading-clone.eprints-hosting.org/id/eprint/17884 |
| Item Type | Article |
| Refereed | Yes |
| Divisions | Science |
| Uncontrolled Keywords | discrete time, linear system, control system, neural network, adaptive control, feedback system, method study, ystem description, parametrization |
| Publisher | Taylor & Francis |
| Download/View statistics | View download statistics for this item |
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