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Advanced Dynamics Modeling, Duality and Control of Robotic Systems [Kõva köide]

(Oakland University, USA.)
  • Formaat: Hardback, 306 pages, kõrgus x laius: 234x156 mm, kaal: 1020 g, 23 Tables, black and white; 77 Line drawings, black and white; 1 Halftones, black and white; 78 Illustrations, black and white
  • Ilmumisaeg: 24-Sep-2021
  • Kirjastus: CRC Press
  • ISBN-10: 0367653710
  • ISBN-13: 9780367653712
Teised raamatud teemal:
Advanced Dynamics Modeling, Duality and Control of Robotic SystemsSuurem pilt
  • Formaat: Hardback, 306 pages, kõrgus x laius: 234x156 mm, kaal: 1020 g, 23 Tables, black and white; 77 Line drawings, black and white; 1 Halftones, black and white; 78 Illustrations, black and white
  • Ilmumisaeg: 24-Sep-2021
  • Kirjastus: CRC Press
  • ISBN-10: 0367653710
  • ISBN-13: 9780367653712
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780367653712.html
Märksõnad:
This book provides detailed fundamental theoretical reviews and preparations necessary for developing advanced dynamics modeling and control strategies for various types of robotic systems. It also presents and discusses the principle of duality involved in robot kinematics, statics, and dynamics.

This book provides detailed fundamental theoretical reviews and preparations necessary for developing advanced dynamics modeling and control strategies for various types of robotic systems. This research book specifically addresses and discusses the uniqueness issue of representing orientation or rotation, and further proposes an innovative isometric embedding approach. The novel approach can not only reduce the dynamic formulation for robotic systems into a compact form, but it also offers a new way to realize the orientational trajectory-tracking control procedures.

In addition, the book gives a comprehensive introduction to fundamentals of mathematics and physics that are required for modeling robot dynamics and developing effective control algorithms. Many computer simulations and realistic 3D animations to verify the new theories and algorithms are included in the book as well.

It also presents and discusses the principle of duality involved in robot kinematics, statics, and dynamics. The duality principle can guide the dynamics modeling and analysis into a right direction for a variety of robotic systems in different types from open serial-chain to closed parallel-chain mechanisms. It intends to serve as a diversified research reference to a wide range of audience, including undergraduate juniors and seniors, graduate students, researchers, and engineers interested in the areas of robotics, control and applications.

Preface xi
Author xiii
Chapter 1 Introduction
1(6)
1.1 Kinematics, Statics and Dynamics
1(1)
1.2 Dynamics Modeling and Model Compaction
2(1)
1.3 The Principle of Duality for Robot Kinematics, Statics and Dynamics
3(1)
1.4 Adaptive and Interactive Control of Robotic Systems
4(1)
1.5 The Organization of the Book
4(3)
Chapter 2 Fundamental Preliminaries
7(72)
2.1 Mathematical Preparations
7(35)
2.1.1 Lie Groups, Lie Algebras and Their Topological Structures
7(7)
2.1.2 Manifolds, Riemannian Metrics, and Embeddings
14(10)
2.1.3 Differential Connections and Geodesic Equations
24(6)
2.1.4 Dual Numbers, Dual Vectors and Dual Matrices
30(12)
2.2 Robot Kinematics: Theories and Representations
42(28)
2.2.1 Unique Representations of Position and Orientation
42(3)
2.2.2 The Rotation Speed and Angular Velocity
45(6)
2.2.3 The Denavit-Hartenberg (D-H) Convention
51(9)
2.2.4 Cartesian Motion vs. Differential Motion
60(5)
2.2.5 Kinematic Singularity and Redundancy
65(5)
2.3 Robot Statics and Applications
70(9)
2.3.1 Twist, Wrench and Statics of Robotic Systems
70(1)
2.3.2 Static Joint Torque Distributions
71(2)
2.3.3 Manipulability and Posture Optimization
73(6)
Chapter 3 Robot Dynamics Modeling
79(40)
3.1 The History of Robot Dynamic Formulations
79(1)
3.2 The Assumption of Rigid Body and Rigid Motion
80(5)
3.2.1 The Rigid Body and Rigid Motion
80(4)
3.2.2 Kinematic Parameters vs. Dynamic Parameters
84(1)
3.3 Kinetic Energy, Potential Energy and Lagrange Equations
85(14)
3.3.1 Determination of Kinetic Energy
85(9)
3.3.2 Potential Energy Due to Gravity and Other Forms
94(3)
3.3.3 Consistency between the Lagrange and Geodesic Equations
97(2)
3.4 Dynamic Formulations for Robotic Systems
99(20)
3.4.1 Determination of Centrifugal and Coriolis Terms
99(4)
3.4.2 Dynamics Modeling for a Variety of Robotic Systems
103(16)
Chapter 4 Advanced Dynamics Modeling
119(26)
4.1 The Configuration Manifold and Isometric Embedding
119(3)
4.2 How to Find an Isometric Embedding
122(12)
4.3 Applications to Robot Dynamics Modeling
134(11)
Chapter 5 The Principle of Duality in Kinematics and Dynamics
145(42)
5.1 Kinematic Structures for Stewart Platform
145(5)
5.2 Kinematic Analysis of Delta Closed Hybrid-Chain Robots
150(9)
5.3 Duality between Open Serial-Chain and Closed Parallel-Chain Systems
159(5)
5.4 Isometric Embedding Based Dynamics Modeling for Parallel and Hybrid-Chain Robots
164(23)
5.4.1 The Stewart Platform
165(1)
5.4.2 The 3D 3-Leg Hybrid-Chain Robotic System
166(8)
5.4.3 The Delta Closed Hybrid-Chain Robot
174(5)
5.4.4 Dynamics Modeling for Legged Robots
179(5)
5.4.5 A Summary of Dynamics Modeling
184(3)
Chapter 6 Nonlinear Control Theories
187(74)
6.1 Lyapunov Stability Theories and Control Strategies
187(18)
6.1.1 The Local Linearization Procedure
197(1)
6.1.2 Indirect Method of Systems Stability Test
198(2)
6.1.3 A Theorem for Determination of System Instability
200(1)
6.1.4 Stabilization of Nonlinear Control Systems
201(4)
6.2 Controllability and Observability
205(6)
6.2.1 Control Lie Algebra and Controllability
206(2)
6.2.2 Observation Space and Observability
208(3)
6.3 Input-State and Input-Output State-Feedback Linearization
211(20)
6.3.1 The Input-State Linearization Procedure
213(5)
6.3.2 Input-Output Mapping, Relative Degrees and Systems Invertibility
218(6)
6.3.3 Systems Invertibility and Applications
224(2)
6.3.4 The Input-Output Linearization Procedure
226(5)
6.4 Isometric Embedding Dynamic Model and Control
231(3)
6.5 Linearizable Subsystems and Internal Dynamics
234(4)
6.6 Control of a Minimum-Phase System
238(3)
6.7 Examples of Partially Linearizable Systems with Internal Dynamics
241(20)
Chapter 7 Adaptive Control of Robotic Systems
261(20)
7.1 The Control Law and Adaptation Law
261(9)
7.2 Applications and Simulation/Animation Studies
270(11)
Chapter 8 Dynamics Modeling and Control of Cascaded Systems
281(22)
8.1 Dynamic Interactions between Robot and Environment
281(3)
8.2 Cascaded Dynamics Models with Backstepping Control Recursion
284(12)
8.2.1 Control Design with the Lyapunov Direct Method
284(5)
8.2.2 Backstepping Recursions in Control Design
289(7)
8.3 Modeling and Interactive Control of Robot-Environment Systems
296(7)
Index 303
Edward Y.L. Gu is currently a Professor with the Department of Electrical and Computer Engineering (ECE), Oakland University, Michigan. He co-founded the OU-Chrysler Robotics and Controls Lab at OU ten years ago.