Linked e-resources
Details
Table of Contents
FUSION OF HARD AND SOFT CONTROL STRATEGIES FOR THE ROBOTIC HAND; Contents; List of Tables; List of Figures; 1 Introduction; 1.1 Relevance to Military; 1.2 Control Strategies; 1.2.1 Prosthetic/Robotic Hands; 1.2.2 Chronological Overview; 1.2.3 Overview of Main Control Techniques Since 2007; 1.2.4 Revolutionary Prosthesis; 1.3 Fusion of Intelligent Control Strategies; 1.3.1 Fusion of Hard and Soft Computing/Control Strategies; 1.4 Overview of Our Research; 1.5 Developments in Neuroprosthetics; 1.6 Chapter Summary; 2 Kinematics and Trajectory Planning; 2.1 Human Hand Anatomy
2.2 Forward Kinematics2.2.1 Homogeneous Transformations; 2.2.2 Serial n Link Revolute Joint Planar Manipulator; 2.2.3 Two Link Thumb; 2.2.4 Three Link Index Finger; 2.2.5 Three Dimensional Five Fingered Robotic Hand; 2.3 Inverse Kinematics; 2.3.1 Two Link Thumb; 2.3.2 Three Link Fingers; 2.3.3 Fingertip Workspace; 2.3.3.1 Two Link Thumb and Three Link Index Finger; 2.3.3.2 Five Fingered Robotic Hand; 2.4 Differential Kinematics; 2.4.1 Serial Link Revolute Joint Planar Manipulator; 2.4.1.1 Some Properties of Rotation Matrices; 2.4.1.2 Rigid Body Kinematics; 2.4.2 Two Link Thumb
2.4.3 Three Link Index Finger2.5 Trajectory Planning; 2.5.1 Trajectory Planning Using Cubic Polynomial; 2.5.2 Trajectory Planning Using Cubic Bézier Curve; 2.5.3 Simulation Results of Trajectory Paths; 3 Dynamic Models; 3.1 Actuators; 3.1.1 Electric DC Motor; 3.1.2 Mechanical Gear Transmission; 3.2 Dynamics; 3.3 Two Link Thumb; 3.4 Three Link Index Finger; 4 Soft Computing/Control Strategies; 4.1 Fuzzy Logic; 4.2 Neural Network; 4.3 Adaptive Neuro Fuzzy Inference System; 4.4 Tabu Search; 4.4.1 Tabu Concepts; 4.4.2 Enhanced Continuous Tabu Search; 4.4.2.1 Initialization of Parameters
4.4.2.2 Diversification4.4.2.3 Selecting the Most Promising Area; 4.4.2.4 Intensification; 4.5 Genetic Algorithm; 4.5.1 Basic GA Procedures; 4.6 Particle Swarm Optimization; 4.6.1 Basic PSO Procedures and Formulations; 4.6.2 Five Different PSO Techniques; 4.6.3 Uniform Distribution and Normal Distribution; 4.7 Adaptive Particle Swarm Optimization; 4.7.1 APSO Procedures and Formulations; 4.7.2 Changed/Unchanged Velocity Direction; 4.8 Condensed Hybrid Optimization; 4.9 Simulation Results and Discussion; 4.9.1 PSO Dynamics Investigation; 4.9.1.1 Benchmark Problems
4.9.1.2 Selection of Parameters4.9.1.3 Simulations; 4.9.2 APSO to Multiple Dimensional Problems; 4.9.3 PSO in Other Biomedical Applications; 4.9.3.1 Leukocyte Adhesion Molecules Modeling; 4.9.4 CHO to Multiple Dimensional Problems; 5 Fusion of Hard and Soft Control Strategies I; 5.1 Feedback Linearization; 5.1.1 State Variable Representation; 5.2 PD/PI/PID Controllers; 5.2.1 PD Controller; 5.2.2 PI Controller; 5.2.3 PID Controller; 5.3 Optimal Controller; 5.3.1 Optimal Regulation; 5.3.2 Linear Quadratic Optimal Control with Tracking System
2.2 Forward Kinematics2.2.1 Homogeneous Transformations; 2.2.2 Serial n Link Revolute Joint Planar Manipulator; 2.2.3 Two Link Thumb; 2.2.4 Three Link Index Finger; 2.2.5 Three Dimensional Five Fingered Robotic Hand; 2.3 Inverse Kinematics; 2.3.1 Two Link Thumb; 2.3.2 Three Link Fingers; 2.3.3 Fingertip Workspace; 2.3.3.1 Two Link Thumb and Three Link Index Finger; 2.3.3.2 Five Fingered Robotic Hand; 2.4 Differential Kinematics; 2.4.1 Serial Link Revolute Joint Planar Manipulator; 2.4.1.1 Some Properties of Rotation Matrices; 2.4.1.2 Rigid Body Kinematics; 2.4.2 Two Link Thumb
2.4.3 Three Link Index Finger2.5 Trajectory Planning; 2.5.1 Trajectory Planning Using Cubic Polynomial; 2.5.2 Trajectory Planning Using Cubic Bézier Curve; 2.5.3 Simulation Results of Trajectory Paths; 3 Dynamic Models; 3.1 Actuators; 3.1.1 Electric DC Motor; 3.1.2 Mechanical Gear Transmission; 3.2 Dynamics; 3.3 Two Link Thumb; 3.4 Three Link Index Finger; 4 Soft Computing/Control Strategies; 4.1 Fuzzy Logic; 4.2 Neural Network; 4.3 Adaptive Neuro Fuzzy Inference System; 4.4 Tabu Search; 4.4.1 Tabu Concepts; 4.4.2 Enhanced Continuous Tabu Search; 4.4.2.1 Initialization of Parameters
4.4.2.2 Diversification4.4.2.3 Selecting the Most Promising Area; 4.4.2.4 Intensification; 4.5 Genetic Algorithm; 4.5.1 Basic GA Procedures; 4.6 Particle Swarm Optimization; 4.6.1 Basic PSO Procedures and Formulations; 4.6.2 Five Different PSO Techniques; 4.6.3 Uniform Distribution and Normal Distribution; 4.7 Adaptive Particle Swarm Optimization; 4.7.1 APSO Procedures and Formulations; 4.7.2 Changed/Unchanged Velocity Direction; 4.8 Condensed Hybrid Optimization; 4.9 Simulation Results and Discussion; 4.9.1 PSO Dynamics Investigation; 4.9.1.1 Benchmark Problems
4.9.1.2 Selection of Parameters4.9.1.3 Simulations; 4.9.2 APSO to Multiple Dimensional Problems; 4.9.3 PSO in Other Biomedical Applications; 4.9.3.1 Leukocyte Adhesion Molecules Modeling; 4.9.4 CHO to Multiple Dimensional Problems; 5 Fusion of Hard and Soft Control Strategies I; 5.1 Feedback Linearization; 5.1.1 State Variable Representation; 5.2 PD/PI/PID Controllers; 5.2.1 PD Controller; 5.2.2 PI Controller; 5.2.3 PID Controller; 5.3 Optimal Controller; 5.3.1 Optimal Regulation; 5.3.2 Linear Quadratic Optimal Control with Tracking System