A Brief Review of Neural Networks Based Learning and Control and Their Applications for Robots
Yiming Jiang,
Chenguang Yang,
Jing Na,
Guang Li,
Yanan Li and
Junpei Zhong
Complexity, 2017, vol. 2017, 1-14
Abstract:
As an imitation of the biological nervous systems, neural networks (NNs), which have been characterized as powerful learning tools, are employed in a wide range of applications, such as control of complex nonlinear systems, optimization, system identification, and patterns recognition. This article aims to bring a brief review of the state-of-the-art NNs for the complex nonlinear systems by summarizing recent progress of NNs in both theory and practical applications. Specifically, this survey also reviews a number of NN based robot control algorithms, including NN based manipulator control, NN based human-robot interaction, and NN based cognitive control.
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://downloads.hindawi.com/journals/8503/2017/1895897.pdf (application/pdf)
http://downloads.hindawi.com/journals/8503/2017/1895897.xml (text/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:1895897
DOI: 10.1155/2017/1895897
Access Statistics for this article
More articles in Complexity from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().