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.
