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Decentralized Identification and Control in Real-Time of a Robot Manipulator via Recurrent Wavelet First-Order Neural Network.
- Source :
-
Mathematical Problems in Engineering . 5/18/2015, Vol. 2015, p1-12. 12p. - Publication Year :
- 2015
-
Abstract
- A decentralized recurrent wavelet first-order neural network (RWFONN) structure is presented. The use of a wavelet Morlet activation function allows proposing a neural structure in continuous time of a single layer and a single neuron in order to identify online in a series-parallel configuration, using the filtered error (FE) training algorithm, the dynamics behavior of each joint for a two-degree-of-freedom (DOF) vertical robot manipulator, whose parameters such as friction and inertia are unknown. Based on the RWFONN subsystem, a decentralized neural controller is designed via backstepping approach. The performance of the decentralized wavelet neural controller is validated via real-time results. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1024123X
- Volume :
- 2015
- Database :
- Academic Search Index
- Journal :
- Mathematical Problems in Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 109250410
- Full Text :
- https://doi.org/10.1155/2015/451049