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Adaptive robust control for planar n-link underactuated manipulator based on radial basis function neural network and online iterative correction method.
- Source :
-
Journal of the Franklin Institute . Nov2018, Vol. 355 Issue 17, p8373-8391. 19p. - Publication Year :
- 2018
-
Abstract
- Abstract This paper presents an adaptive robust control strategy based on a radial basis function neural network (RBFNN) and an online iterative correction method (OICM) for a planar n -link underactuated manipulator with a passive first joint to realize its position control objective. An uncertain model of the planar n -link underactuated manipulator is built, which contains the parameter perturbation and the external disturbance. The adaptive robust controllers based on the RBFNN are designed to realize the model reduction, which makes the system reduce to a planar virtual three-link underactuated manipulator (PVTUM) and simplifies the complexity of the system control. An online differential evolution (DE) algorithm is used to calculate the target angles of the PVTUM based on the nominal model parameters. The control of the PVTUM is divided into two stages, and the adaptive robust controllers are still employed to realize the control objective of each stage. Then, the OICM is used to correct the deviations of all link angles of the PVTUM caused by the parameter perturbation, which makes the end-point of the system gradually approach to its target position. Finally, simulation results of a planar four-link underactuated manipulator demonstrate the effectiveness of the proposed adaptive robust control strategy. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00160032
- Volume :
- 355
- Issue :
- 17
- Database :
- Academic Search Index
- Journal :
- Journal of the Franklin Institute
- Publication Type :
- Periodical
- Accession number :
- 132754513
- Full Text :
- https://doi.org/10.1016/j.jfranklin.2018.08.022