[正版书籍]永磁球形电机--基于模型以及物理场的设计、传感和控制(英文版)

Rapid advances of intelligent machines for amsrt manufacturing equipment,driverless vehicles,robotics,and medical industries continue to motivate new designs and app;ocations of multi-degree-of-freedom(DOF) actuators capable of complex motion and precise force/torque manipulations to complete tasks that have never been automated before.Extensive efforts to develop novel actuators with compact designs and designs and dexterous manipulations can be found in both academic research and indusrial development.Unlike multi-DOF systems with designs based on bulky serial/parallel combinations cf single-axis spin motors and transmission mechanisms,spherical motors/actuators are direct-drive and can achieve multi-DOF rotational motions in a single ball joint,because of these attractive features,along with the structural simplicity and the capability to achieve quick singularity-free motion,spherical motors are expected to play a significant role in the developmet of intelligent machines.

CHAPTER 1 INTRODUCTION/1

1.1Background/1

1.2The State of the Art/3

1.21 Marnetic Modeling and Analysis/6

1.22 Orientation Sensing/8

1.23 Control Methods/10

1.3 Book Outline/12

PART I MODELLING METHODS FOR PMSMS/21

CHAPTER 2 General Formulation OF PMSMs/21

2.1 PMSM Electromagnetic System Modeling/21

2.1.1 Governing Equations of Electromagnetic Field/21

2.1.2 Boundary Condition/24

2.1.3 Magnetic Flux Linkage and Energy/25

2.1.4 Magnetic Force/Torque/26

2.2 PMSM Rotor Dynamic /27

References/30

CHAPTER 3 Distributed Multi-Pole Models/31

3.1 Distributed Multi-Pole Model for PMs/31

3.1.1 PM Field with DMP Model/32

3.1.2 Numerical Illustrative Examples/35

3.2 Distributed Multi-Pole Model for EMs/43

3.2.1 Equivalent Magnetization of the ePM/45

3.2.2 Illustrations of Magnetic Field Computation/47

3.3 Dipole Force/Torque Model/47

3.3.1 Force and Torque on a Magnetic Dipole/47

3.3.2 Illustration of Magnetic Force Computation/49

3.4 Image Method with DMP Models/52

3.4.1 Image Method with Spherical Grounded Boundary/53

3.4.2 Illustrative Examples/56

3.4.3 Effects of Iron Boundary on the Torque/58

3.5 Illustrative Numerical Simulations for PMSM Design/62

3.5.1 Pole Pair Design/65

3.5.2 Static Loading Investigation/70

3.5.3 Weight-Compensating Regulator/71

References/79

CHAPTER 4 PMSM Force/Torque Model for Real-Time Control/81

4.1 Force/Torque Formulation/81

4.1.1 Magnetic Force/Torque Based on The Kernel Functions/82

4.1.2 Simplified Model: Axis-Symmetric EMs/PMs/85

4.1.3 Inverse Torque Model/86

4.2 Numerical Illustrations/86

4.2.1 Axis-Asymmetric EM/PMs/86

4.2.2 Axis-Symmetric EM/PM/90

4.3 Illustrative PMSM Torque Modelling /93

PART II SENSING Methods

CHAPTER 5 Field-Based Orientation Sensing/99

5.1 Coordinate Systems and Sensor Placement/99

5.2 Field Mapping and Segmentation/100

5.3 Artificial Neural Network Inverse Map/102

5.4 Experimental Investigation/103

5.4.1 2-DOF Concurrent Characterization/104

References/107

CHAPTER 6 A Back-EMF Method for Multi-DOF Motion Detection/109

6.1 Back-EMF for Multi-DOF Motion Sensing/109

6.1.1 EMF Model in a Single EM-PM pair/111

6.1.2 Back-EMF with Multiple EM-PM pairs/112

6.2 Implementation of Back-EMF Method on a PMSM/114

6.2.1 Mechanical and Magnetic Structure of the PMSM/115

6.2.2 Numerical Solutions for the MFL Model/116

6.2.3 Experiment and Discussion/118

6.2.4 Parameter Estimation of the PMSM with back-EMF Method/120

References/122

PART III CONTROL METHODS

CHAPTER 7 Direct Field-Feedback Ccontrol/125

7.1 Traditional Orientation Control Method for Spherical Motors/125

7.1.1 PD Control Law and Stability Analysis/126

7.1.2 Comments on Implementation of Traditional Control Methods/127

7.2 Direct Field-Feedback Control/128

7.2.1 Determination of Bijective Domain/129

7.2.2 DFC Control Law and Control Parameter Determination/129

7.2.3 DFC with Multi-sensors/130

7.3 Numerical 1-DOF Illustrative Example/131

7.3.1 Sensor Design and Bijective Domain Identification/131

7.3.2 Field-based Control Law/133

7.3.3 Numerical Illustrations of Multiple Bijective Domains/135

7.4 Experimental Investigation of DFC for 3-DOF PMSM/135

7.4.1 System Description/135

7.4.2 Sensor Design and Bijective Domains/138

7.4.3 Bijective domain/139

7.4.4 TCV Computation Using Artificial Neural Network (ANN)/142

7.4.5 Experimental Investigation/142

References/150

CHAPTER 8 A Two-mode PMSM for Haptic Applications/151

8.1 Description of the PMSM Haptic Device/151

8.1.1 Two-mode configuration Design for 6-DOF Manipulation/153

8.1.2 Numerical Model for Magnetic Field/Torque Computation/154

8.1.3 Field-based TCV Estimation/155

8.2 Snap-Fit Simulation/156

8.2.1 Snap-Fit Performance Analyses/158

8.2.2 Snap-Fit Haptic Application/159

References/164

This book introduces and illustrates modeling, sensing, and control methods for analyzing, designing, and developing spherical motors. It systematically presents modelsfor establishing the relationships among the magnetic fields position/orientation and force/torque, while also providing time-efficient solutions to assist researchers and engineers in studying and developing these motors. In order to take full advantage of spherical motors’ compact structure in practical applications, sensing and control methods that utilize their magnetic fields and eliminate the need to install external sensors for feedback are proposed. Further, the book investigates for the first time spherical motors’force/torque manipulation capability, and proposes algorithms enabling the ball-joint-like end-effector for haptic use based on these motors’hybrid position/force actuation modes. While systematically presenting approaches to their design, sensing and control, the book also provides many examples illustrating the implementation issues readers may encounter.

白坤，男，博士，华中科技大学副教授。本科毕业于浙江大学控制科学与工程系；2012年于美国佐治亚理工学院(Georgia Institute ofTechnology)机械系取得博士学位；目前在数字制造装备与技术国家重点实验室进行科研工作。?? ? 主要从事机电系统、控制系统、驱动器和传感的研究，相关成果发表SCI、EI收录文章20余次，目前主持国家自然科学基金项目2项，作为主要成员参加国家重点基础研究发展计划（973）项目1项。担任IEEE和ASME多个期刊和会议的审稿人，也多次在国际会议做报告并受邀担任分会主席。?? 李国民，美国麻省理工学院博士，美国总统奖获得者，IEEE Fellow、ASME Fellow、IEEE/ASME Transactions on Mechatronics（TMech）主编 (2008-2013)。美国佐治亚理工学院任终身教授、华中科技大学教授，973项目首席科学家。主要研究领域为智能制造装备与技术、智能传感及驱动、复杂机电系统。主持与智能制造密切相关的美国自然科学基金、国际合作项目十余项。在智能传感器、灵巧驱动器、机器视觉、多变量热-流耦合过程建模与控制等领域取得系列成果，并广泛应用于制造工业中的检测、定位与控制、场重构、分布参数建模与控制等方面。发表相关论文250余篇，参与出版英文专著3部，授权美国与国际专利10项。于2008创立TMech Best Paper Award，同年作为IEEE/ASME AIM国际会议的共同成立者，受ASME/DSCD-Mechatronics TC（机电一体化委员会）支持，创立 (Best Paper and Best Student Paper Awards in Mechatronics) 两个奖项。