A Brief Review of Neural Networks Based Learning and Control and Their Applications for Robots. (31st October 2017)

• Record Type: Journal Article
• Authors: Jiang, Yiming; Yang, Chenguang; Na, Jing; Li, Guang; Li, Yanan; Zhong, Junpei
• Other Names: Floquet Thierry Academic Editor.
• Is Part Of: Complexity. Volume 2017(2017)
• Publication Date: 2017-10-31
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2017/1895897
• Languages: English
• ISSNs: 1076-2787

Abstract

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.