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 motorsforce/torque manipulation capability, and proposes algorithms enabling the ball-joint-like end-effector for haptic use based on these motorshybrid 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.
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.
白坤,男,博士,華中科技大學(xué)副教授。本科畢業(yè)于浙江大學(xué)控制科學(xué)與工程系;2012年于美國佐治亞理工學(xué)院(Georgia Institute ofTechnology)機械系取得博士學(xué)位;目前在數(shù)字制造裝備與技術(shù)國家重點實驗室進(jìn)行科研工作。?? ? 主要從事機電系統(tǒng)、控制系統(tǒng)、驅(qū)動器和傳感的研究,相關(guān)成果發(fā)表SCI、EI收錄文章20余次,目前主持國家自然科學(xué)基金項目2項,作為主要成員參加國家重點基礎(chǔ)研究發(fā)展計劃(973)項目1項。擔(dān)任IEEE和ASME多個期刊和會議的審稿人,也多次在國際會議做報告并受邀擔(dān)任分會主席。?? 李國民,美國麻省理工學(xué)院博士,美國總統(tǒng)獎獲得者,IEEE Fellow、ASME Fellow、IEEE/ASME Transactions on Mechatronics(TMech)主編 (2008-2013)。美國佐治亞理工學(xué)院任終身教授、華中科技大學(xué)教授,973項目首席科學(xué)家。主要研究領(lǐng)域為智能制造裝備與技術(shù)、智能傳感及驅(qū)動、復(fù)雜機電系統(tǒng)。主持與智能制造密切相關(guān)的美國自然科學(xué)基金、國際合作項目十余項。在智能傳感器、靈巧驅(qū)動器、機器視覺、多變量熱-流耦合過程建模與控制等領(lǐng)域取得系列成果,并廣泛應(yīng)用于制造工業(yè)中的檢測、定位與控制、場重構(gòu)、分布參數(shù)建模與控制等方面。發(fā)表相關(guān)論文250余篇,參與出版英文專著3部,授權(quán)美國與國際專利10項。于2008創(chuàng)立TMech Best Paper Award,同年作為IEEE/ASME AIM國際會議的共同成立者,受ASME/DSCD-Mechatronics TC(機電一體化委員會)支持,創(chuàng)立 (Best Paper and Best Student Paper Awards in Mechatronics) 兩個獎項。
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