Neural Networks for Cooperative Control of Multiple Robot Arms (SpringerBriefs in Applied Sciences and Technology) - Softcover

Über die Autorin bzw. den Autor

Shuai Li received the B.E. degree in Precision Mechanical Engineering from Hefei University of Technology, China in 2005, the M.E. degree in Automatic Control Engineering from University of Science and Technology of China, China in 2008, and the Ph.D. degree in Electrical and Computer Engineering from Stevens Institute of Technology, USA in 2014. He is currently affiliated with Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong. His main research interests include neural networks, robotics, control of networked systems, computation and optimization. He has been working on the research and application of neural networks/dynamics for 12 years. He has published more than 80 scientific works of various types. These include 20 IEEE-Transactions papers, and 60 SCI-indexed papers published in recent 5 years. The number of papers’ citations shown via Google Scholar Search is 807. He is now serving as associate editors of International Journal ofAdvanced Robotic Systems, Frontiers in Neurorobotics, Neural Processing Letters, Journal of Rehabilitation Robotics and editorial board members of International Journal of Distributed Sensor Networks and Neural Computation & Applications.

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).

Von der hinteren Coverseite

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.