Kinematic Control of Redundant Robot Arms Using Neural Networks :
General Material Designation
[Book]
Other Title Information
a Theoretical Study.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Newark :
Name of Publisher, Distributor, etc.
John Wiley & Sons, Incorporated,
Date of Publication, Distribution, etc.
2019.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (217 pages)
GENERAL NOTES
Text of Note
6.5.3 Convergence Analysis
CONTENTS NOTE
Text of Note
Intro; Title Page; Copyright Page; Contents; List of Figures; List of Tables; Preface; Acknowledgments; Part I Neural Networks for Serial Robot Arm Control; Chapter 1 Zeroing Neural Networks for Control; 1.1 Introduction; 1.2 Scheme Formulation and ZNN Solutions; 1.2.1 ZNN Model; 1.2.2 Nonconvex Function Activated ZNN Model; 1.3 Theoretical Analyses; 1.4 Computer Simulations and Verifications; 1.4.1 ZNN for Solving (1.13) at t = 1; 1.4.2 ZNN for Solving (1.13) with Different Bounds; 1.5 Summary; Chapter 2 Adaptive Dynamic Programming Neural Networks for Control; 2.1 Introduction
Text of Note
2.2 Preliminaries on Variable Structure Control of the Sensor-Actuator System2.3 Problem Formulation; 2.4 Model-Free Control of the Euler-Lagrange System; 2.4.1 Optimality Condition; 2.4.2 Approximating the Action Mapping and the Critic Mapping; 2.5 Simulation Experiment; 2.5.1 The Model; 2.5.2 Experiment Setup and Result; 2.6 Summary; Chapter 3 Projection Neural Networks for Robot Arm Control; 3.1 Introduction; 3.2 Problem Formulation; 3.3 A Modified Controller without Error Accumulation; 3.3.1 Existing RNN Solutions; 3.3.2 Limitations of Existing RNN Solutions; 3.3.3 The Presented Algorithm
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3.3.4 Stability3.4 Performance Improvement Using Velocity Compensation; 3.4.1 A Control Law with Velocity Compensation; 3.4.2 Stability; 3.5 Simulations; 3.5.1 Regulation to a Fixed Position; 3.5.2 Tracking of Time-Varying References; 3.5.3 Comparisons; 3.6 Summary; Chapter 4 Neural Learning and Control Co-Design for Robot Arm Control; 4.1 Introduction; 4.2 Problem Formulation; 4.3 Nominal Neural Controller Design; 4.4 A Novel Dual Neural Network Model; 4.4.1 Neural Network Design; 4.4.2 Stability; 4.5 Simulations; 4.5.1 Simulation Setup; 4.5.2 Simulation Results; 4.5.2.1 Tracking Performance
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4.5.2.2 With vs. Without Excitation Noises4.6 Summary; Chapter 5 Robust Neural Controller Design for Robot Arm Control; 5.1 Introduction; 5.2 Problem Formulation; 5.3 Dual Neural Networks for the Nominal System; 5.3.1 Neural Network Design; 5.3.2 Convergence Analysis; 5.4 Neural Design in the Presence of Noises; 5.4.1 Polynomial Noises; 5.4.1.1 Neural Dynamics; 5.4.1.2 Practical Considerations; 5.4.2 Special Cases; 5.4.2.1 Constant Noises; 5.4.2.2 Linear Noises; 5.5 Simulations; 5.5.1 Simulation Setup; 5.5.2 Nominal Situation; 5.5.3 Constant Noises; 5.5.4 Time-Varying Polynomial Noises
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5.6 SummaryChapter 6 Using Neural Networks to Avoid Robot Singularity; 6.1 Introduction; 6.2 Preliminaries; 6.3 Problem Formulation; 6.3.1 Manipulator Kinematics; 6.3.2 Manipulability; 6.3.3 Optimization Problem Formulation; 6.4 Reformulation as a Constrained Quadratic Program; 6.4.1 Equation Constraint: Speed Level Resolution; 6.4.2 Redefinition of the Objective Function; 6.4.3 Set Constraint; 6.4.4 Reformulation and Convexification; 6.5 Neural Networks for Redundancy Resolution; 6.5.1 Conversion to a Nonlinear Equation Set; 6.5.2 Neural Dynamics for Real-Time Redundancy Resolution
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Title
Kinematic Control of Redundant Robot Arms Using Neural Networks : A Theoretical Study.