TY - JOUR
T1 - A brief review of neural networks based learning and control and their applications for robots
AU - Jiang, Yiming
AU - Yang, Chenguang
AU - Na, Jing
AU - Li, Guang
AU - Li, Yanan
AU - Zhong, Junpei
N1 - Funding Information:
This work was partially supported by the National Nature Science Foundation (NSFC) under Grant 61473120, Guangdong Provincial Natural Science Foundation, 2014A030313266, International Science and Technology Collaboration, Grant 2015A050502017, Science and Technology Planning Project of Guangzhou, 201607010006, State Key Laboratory of Robotics and System (HIT) Grant SKLRS-2017-KF-13, and the Fundamental Research Funds for the Central Universities.
Publisher Copyright:
© 2017 Yiming Jiang et al.
PY - 2017/10/31
Y1 - 2017/10/31
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85042379030&partnerID=8YFLogxK
U2 - 10.1155/2017/1895897
DO - 10.1155/2017/1895897
M3 - Review article
AN - SCOPUS:85042379030
SN - 1076-2787
VL - 2017
JO - Complexity
JF - Complexity
M1 - 1895897
ER -