Cover image for Kinematic Control of Redundant Robot Arms Using Neural Networks

Kinematic Control of Redundant Robot Arms Using Neural Networks

Author Mohammed Aquil Mirza , Long Jin , Shuai Li
Release Date: 2019/04/01
ISBN: 9781119556961
Topic:
0%
25
Chapters
0-1
Hours read
0k
Total Words
    Start Reading Now    
       Add to Wishlist       
View table of contents

Book Description

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.

Table of Contents

  1. Cover
  2. List of Figures
  3. List of Tables
  4. Preface
  5. Acknowledgments
  6. Part I: Neural Networks for Serial Robot Arm Control
    1. 1 Zeroing Neural Networks for Control
      1. 1.1 Introduction
      2. 1.2 Scheme Formulation and ZNN Solutions
      3. 1.3 Theoretical Analyses
      4. 1.4 Computer Simulations and Verifications
      5. 1.5 Summary
    2. 2 Adaptive Dynamic Programming Neural Networks for Control
      1. 2.1 Introduction
      2. 2.2 Preliminaries on Variable Structure Control of the Sensor–Actuator System
      3. 2.3 Problem Formulation
      4. 2.4 Model‐Free Control of the Euler–Lagrange System
      5. 2.5 Simulation Experiment
      6. 2.6 Summary
    3. 3 Projection Neural Networks for Robot Arm Control
      1. 3.1 Introduction
      2. 3.2 Problem Formulation
      3. 3.3 A Modified Controller without Error Accumulation
      4. 3.4 Performance Improvement Using Velocity Compensation
      5. 3.5 Simulations
      6. 3.6 Summary
    4. 4 Neural Learning and Control Co‐Design for Robot Arm Control
      1. 4.1 Introduction
      2. 4.2 Problem Formulation
      3. 4.3 Nominal Neural Controller Design
      4. 4.4 A Novel Dual Neural Network Model
      5. 4.5 Simulations
      6. 4.6 Summary
    5. 5 Robust Neural Controller Design for Robot Arm Control
      1. 5.1 Introduction
      2. 5.2 Problem Formulation
      3. 5.3 Dual Neural Networks for the Nominal System
      4. 5.4 Neural Design in the Presence of Noises
      5. 5.5 Simulations
      6. 5.6 Summary
    6. 6 Using Neural Networks to Avoid Robot Singularity
      1. 6.1 Introduction
      2. 6.2 Preliminaries
      3. 6.3 Problem Formulation
      4. 6.4 Reformulation as a Constrained Quadratic Program
      5. 6.5 Neural Networks for Redundancy Resolution
      6. 6.6 Illustrative Examples
      7. 6.7 Summary
  7. Part II: Neural Networks for Parallel Robot Control
    1. 7 Neural Network Based Stewart Platform Control
      1. 7.1 Introduction
      2. 7.2 Preliminaries
      3. 7.3 Robot Kinematics
      4. 7.4 Problem Formulation as Constrained Optimization
      5. 7.5 Dynamic Neural Network Model
      6. 7.6 Theoretical Results
      7. 7.7 Numerical Investigation
      8. 7.8 Summary
    2. 8 Neural Network Based Learning and Control Co‐Design for Stewart Platform Control
      1. 8.1 Introduction
      2. 8.2 Kinematic Modeling of Stewart Platforms
      3. 8.3 Recurrent Neural Network Design
      4. 8.4 Numerical Investigation
      5. 8.5 Summary
  8. Part III: Neural Networks for Cooperative Control
    1. 9 Zeroing Neural Networks for Robot Arm Motion Generation
      1. 9.1 Introduction
      2. 9.2 Preliminaries
      3. 9.3 Problem Formulation and Distributed Scheme
      4. 9.4 NTZNN Solver and Theoretical Analyses
      5. 9.5 Illustrative Examples
      6. 9.6 Summary
    2. 10 Zeroing Neural Networks for Robot Arm Motion Generation
      1. 10.1 Introduction
      2. 10.2 Preliminaries, Problem Formulation, and Distributed Scheme
      3. 10.3 NANTZNN Solver and Theoretical Analyses
      4. 10.4 Illustrative Examples
      5. 10.5 Summary
  9. References
  10. Index
  11. End User License Agreement
3.146.176.88