Overview
- Is the first book to focus on solving cooperative control problems of multiple robot arms using different centralized or distributed neural network models
- Includes both theoretical analyses of the models and simulated examples of industrial robot arms
- Is suitable for undergraduate and postgraduate students, as well as academic and industrial researchers from various fields of neural networks, robotics, control, simulation and modeling
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)
Part of the book sub series: SpringerBriefs in Computational Intelligence (BRIEFSINTELL)
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Table of contents (4 chapters)
Keywords
About this book
This is the first book to focus on solving cooperative control problems of multiple robot arms using different centralized or distributed neural network models, presenting methods and algorithms together with the corresponding theoretical analysis and simulated examples. It is intended for graduate students and academic and industrial researchers in the field of control, robotics, neural networks, simulation and modelling.
Authors and Affiliations
About the authors
Yinyan Zhang received the B.E. degree from Sun Yat-sen University, Guangzhou, China. He is currently a PhD student at the Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong. His main research interests include nonlinear systems, dynamic neural networks, and robotics. He has published more than 20 scientific papers as author or co-author (including 7 IEEE-transaction papers).
Bibliographic Information
Book Title: Neural Networks for Cooperative Control of Multiple Robot Arms
Authors: Shuai Li, Yinyan Zhang
Series Title: SpringerBriefs in Applied Sciences and Technology
DOI: https://doi.org/10.1007/978-981-10-7037-2
Publisher: Springer Singapore
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Author(s) 2018
Softcover ISBN: 978-981-10-7036-5Published: 10 November 2017
eBook ISBN: 978-981-10-7037-2Published: 29 October 2017
Series ISSN: 2191-530X
Series E-ISSN: 2191-5318
Edition Number: 1
Number of Pages: XV, 74
Number of Illustrations: 4 b/w illustrations, 22 illustrations in colour
Topics: Control, Robotics, Mechatronics, Mathematical Models of Cognitive Processes and Neural Networks, Simulation and Modeling, Computational Intelligence, Computational Science and Engineering