Control of Flexible-link Manipulators Using Neural Networks addresses the difficulties that arise in controlling the end-point of a manipulator that has a significant amount of structural flexibility in its links. The non-minimum phase characteristic, coupling effects, nonlinearities, parameter variations and unmodeled dynamics in such a manipulator all contribute to these difficulties. Control strategies that ignore these uncertainties and nonlinearities generally fail to provide satisfactory closed-loop performance. This monograph develops and experimentally evaluates several intelligent (neural network based) control techniques to address the problem of controlling the end-point of flexible-link manipulators in the presence of all the aforementioned difficulties. To highlight the main issues, a very flexible-link manipulator whose hub exhibits a considerable amount of friction is considered for the experimental work. Four different neural network schemes are proposed and implemented on the experimental test-bed. The neural networks are trained and employed as online controllers.
| Autorius: | H. A. Talebi, K. Khorasani, R. V. Patel, |
| Serija: | Lecture Notes in Control and Information Sciences |
| Leidėjas: | Springer London |
| Išleidimo metai: | 2001 |
| Knygos puslapių skaičius: | 168 |
| ISBN-10: | 1852334096 |
| ISBN-13: | 9781852334093 |
| Formatas: | 233 x 155 x 10 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
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