Kinematic Control of Redundant Robot Arms Using Neural Networks
Language: English
Published by John Wiley and Sons Inc, US, 2019
- Hardcover
- New
Seller: Rarewaves.com USA, London, London, United KingdomRarewaves.com USA
AbeBooks seller since June 11, 2025
Condition: New
£ 117.72
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Add to basketItem description from seller
Presents pioneering and comprehensive work on engaging movement in robotic arms, with a specific focus on neural networks This book presents and investigates different methods and schemes for the control of robotic arms whilst exploring the field from all angles. On a more specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations. Kinematic Control of Redundant Robot Arms Using Neural Networks is divided into three parts: Neural Networks for Serial Robot Arm Control; Neural Networks for Parallel Robot Control; and Neural Networks for Cooperative Control. The book starts by covering zeroing neural networks for control, and follows up with chapters on adaptive dynamic programming neural networks for control; projection neural networks for robot arm control; and neural learning and control co-design for robot arm control. Next, it looks at robust neural controller design for robot arm control and teaches readers how to use neural networks to avoid robot singularity. It then instructs on neural network based Stewart platform control and neural network based learning and control co-design for Stewart platform control. The book finishes with a section on zeroing neural networks for robot arm motion generation. Provides comprehensive understanding on robot arm control aided with neural networksPresents neural network-based control techniques for single robot arms, parallel robot arms (Stewart platforms), and cooperative robot armsProvides a comparison of, and the advantages of, using neural networks for control purposes rather than traditional control based methodsIncludes simulation and modelling tasks (e.g., MATLAB) for onward application for research and engineering development By focusing on robot arm control aided by neural networks whilst examining central topics surrounding the field, Kinematic Control of Redundant Robot Arms Using Neural Networks is an excellent book for graduate students and academic and industrial researchers studying neural dynamics, neural networks, analog and digital circuits, mechatronics, and mechanical engineering.…
Seller Inventory # LU-9781119556961
- Title
- Kinematic Control of Redundant Robot Arms Using Neural Networks
- Author
- Shuai Li, Long Jin, Mohammed Aquil Mirza
- Publisher
- John Wiley and Sons Inc, US
- Publication year
- 2019
- Condition
- New
- Binding
- Hardback
- Language
- English
- ISBN 10
- 1119556961
- ISBN 13
- 9781119556961
- Item weight
- 482 grams
Presents pioneering and comprehensive work on engaging movement in robotic arms, with a specific focus on neural networks
This book presents and investigates different methods and schemes for the control of robotic arms whilst exploring the field from all angles. On a more specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations.
Kinematic Control of Redundant Robot Arms Using Neural Networks is divided into three parts: Neural Networks for Serial Robot Arm Control; Neural Networks for Parallel Robot Control; and Neural Networks for Cooperative Control. The book starts by covering zeroing neural networks for control, and follows up with chapters on adaptive dynamic programming neural networks for control; projection neural networks for robot arm control; and neural learning and control co-design for robot arm control. Next, it looks at robust neural controller design for robot arm control and teaches readers how to use neural networks to avoid robot singularity. It then instructs on neural network based Stewart platform control and neural network based learning and control co-design for Stewart platform control. The book finishes with a section on zeroing neural networks for robot arm motion generation.
- Provides comprehensive understanding on robot arm control aided with neural networks
- Presents neural network-based control techniques for single robot arms, parallel robot arms (Stewart platforms), and cooperative robot arms
- Provides a comparison of, and the advantages of, using neural networks for control purposes rather than traditional control based methods
- Includes simulation and modelling tasks (e.g., MATLAB) for onward application for research and engineering development
By focusing on robot arm control aided by neural networks whilst examining central topics surrounding the field, Kinematic Control of Redundant Robot Arms Using Neural Networks is an excellent book for graduate students and academic and industrial researchers studying neural dynamics, neural networks, analog and digital circuits, mechatronics, and mechanical engineering.
"Synopsis" may belong to another edition of this title.
About the Author
SHUAI LI, PhD, is Assistant Professor in the Department of Computing at the Hong Kong Polytechnic University.
LONG JIN, PhD, is Postdoctoral Fellow in the Department of Computing at the Hong Kong Polytechnic University.
MOHAMMED AQUIL MIRZA, M.S., is a Doctorate Research Scholar with Hong Kong Polytechnic University.
"About the title" may belong to another edition of this title.
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