摘要
具有多种感知功能的仿人机器人灵巧手是机器人领域中一个重要的研究方向。本文结合国家科技部(863计划)项目“新一代五指仿人灵巧手及其协调控制的研究”(课题编号:2006AA04Z255),在哈工大机器人研究所与德宇航中心联合研制的HIT/DLR I灵巧手基础上进行改进,目标是实现与人手相近的外形和尺寸(HIT/DLR I灵巧手为1.5倍人手大小,且仅有四个手指),研制达到国际领先水平的驱动内置型五指仿人灵巧手,并重点进行单手指位置控制和柔顺控制的研究以及基于该灵巧手进行多指协调操作的研究。
为了能够代替人手完成复杂的任务,要求灵巧手具有与人手相似的大小和活动能力,这由执行机构、驱动控制系统和传感器系统的机械机构所决定。此外,灵巧手还须具有与人手类似的操作能力,如执行精细抓取操作时要求手指具有足够的位置精度,对易碎物体的抓取时要有足够的力控制精度,同时由于环境的不确定性,要求灵巧手具有一定的抗干扰能力,以保证对物体的稳定抓取,这些均对灵巧手控制系统的性能提出了严格的要求。
为了提高灵巧手的集成度并增强控制性能,本文研制了基于DSP/FPGA控制结构的模块化嵌入式手指控制系统,成功地将手指驱动系统集成在手指内部,使得与人手尺寸和活动性相似的HIT/DLR II五指机器人灵巧手的得以实现。为实现电机相电流检测,采用一个电流传感器测量并重构了三相电流,并通过设定采样时间获得了稳定的电流信号。为解决手指DSP和FPGA之间如何稳定、高效通信的难题,结合先进先出寄存器,设计了基于串行通信接口和RS485总线的多中断差分通信系统。为了提高灵巧手的智能化水平,HIT/DLR II灵巧手集成了多个微型传感器,所有传感器的模拟输出就近转化为数字信号,以减小信号长距离传输引起的噪声干扰。
针对传统巨磁阻传感器在小于1.5 mm工作距离可能引起信号失真或传感器损坏的问题,基于三维静态磁场分析技术分析了不同类型的永磁铁磁场分布,为高度集成的HIT/DLR II五指机器人灵巧手开发了工作距离为0.5 mm的微型巨磁阻传感器系统。实践结果表明经非线性误差补偿后巨磁阻传感器角度测量精度可达±1o。此外,所开发的巨磁阻传感器系统与传统的传感器系统相比,还具有结构简单、成本低、集成度高、精度高的特点,为其它微机电系统和高集成系统的微型磁传感器研究建立了良好的基础。
针对HIT/DLR II五指机器人灵巧手手指结构,本文建立了驱动空间中基关节交叉耦合同步误差和关节空间中主从同步误差表达式,提出了包含同步误差和位置误差反馈项及平滑鲁棒非线性反馈补偿项的同步位置控制策略,并理论证明了该策略能够使同步误差和位置误差均收敛,且具有渐近稳定性。通过与非同步控制的PD加摩擦力补偿算法和轨迹跟踪控制算法进行对比,表明文中所设计的控制器有效地提高了指尖在自由空间中的轨迹跟踪精度。
通过将关节力矩传感器的反馈信号转化为位置修正向量,本文建立了驱动空间中基关节交叉耦合同步误差和关节空间中主从同步误差表达式,提出了包含同步误差和位置误差反馈项及平滑鲁棒非线性反馈补偿项的同步阻抗控制策略。基于李雅普诺夫稳定性理论证明了所提出的控制策略能够使同步误差和位置误差均收敛,并且保证了系统的渐近稳定性。经与非同步控制的PID阻抗控制算法进行对比,验证了所提出控制策略的有效性,同时与人手的相互作用实验,可以看出设计的同步阻抗控制器能够根据感应到的力矩产生柔顺的光滑运动,表明该系统获得了理想的阻抗性能,为多指手的抓握和与人协调操作奠定了基础。
针对灵巧手在不确定环境工作中有可能碰到障碍或受到外界干扰,从而发生被抓物体脱离或损坏的情况,建立了笛卡尔空间多指同步误差表达式,提出了笛卡尔空间多指同步阻抗控制算法,将受干扰手指与其它未受干扰手指的运动联系起来,保持了相对的抓取平衡状态。基于李雅普诺夫稳定性理论证明了所提出的控制策略能够保证系统的渐近稳定性。实验表明该控制策略避免了被抓取物体的脱离或损坏,从而大大提高抓取的抗干扰能力。
Dexterous robot hand which has the function of multiform perception is main aspects of robot research. Based on national high technique program (863)“Research on new genetation five-fingerd anthropopathic dexterous robot hand and its cooperative control”, it is the improvement of HIT/DLR I robot hand, and the aim is to accomplish the five-finger HIT/DLR II dexterous robot hand that resembles the human hand regarding size and movability (HIT/DLR I robot hand about 1.5 the size of human hand with only four fingers). The dissertation emphasizes on position control and compliance control of a finger and coordinated grasping manipulative strategy of multiple fingers.
To replace human hand, the robot has to fulfill the following requisites: first the robot hand must resemble the human hand regarding size and movability. This determines the hardware, i.e. the mechanical structure, actuator and sensor system. Second the robot hand must have skills and a sleight of hand comparable to the human hand. For example, the hand must be both have enough position accuracy in fine grasping manipulation, and enough force accuracy when grasp fragile object. Moreover, it requires the ability of anti-interference in uncertain environment. This determines the software, i.e. the desired performance of the control system.
In order to develop five-finger dexterous robot hand with high integration, a DSP&FPGA-based multilevel control system is developed for multi-sensory and multi-DOF dexterous robot hand, in which the drive, control and sensor systems are integrated in the finger. So the five-finger HIT/DLR II dexterous robot hand that resembles the human hand regarding size and movability is realized. To accomplish the phase current detection of the motor, a single direct current link current sensor is used to measure and reconstruct the three phase currents, and stable current signal is measured by optimizing sample instant. To solve the problem of efficient and reliable communication between finger DSP and FPGA, a kind of multi-interrupt differential communication system based on serial communications interface (SCI) and RS485 bus using first in first out (FIFO) registers is designed. To enhance the levels of intelligence manipulation, HIT/DLR II robot hand is equipped with multiple sensors, and all the analog signals are converted in-situ into digital signals to minish noise interference.
To solve the problem that the working distance of traditional giant magnetoresistance (GMR) sensor must be more than 1.5 mm, or else it maycause severe disorientation of the angular measurement or permanently damage the sensor element. Based on 3D static magnetic analysis technique, a method for the modeling of ferromagnetic component of the sensor system is presented, and the ultra-miniature giant magnetoresistance sensor system with only 0.5 mm working distance is newly developed for highly integrated HIT/DLR II five-finger dexterous robot hand. The experimental results show an angular accuracy of less than±1°with only the residual offset compensation of ultra-miniature GMR sensor system is obtained. It also has the qualities of simple structure, low cost, ultra-miniature size, and high accuracy, all of which makes up for the shortcomings of traditional measurement sensors.
According to the finger structure, a cross-couple synchronized error expression in drive space and master-slave synchronized error expression in joint space are built for HIT/DLR II robot finger. Then a synchronized position control approach is present, including feedbacks of synchronous errors and position errors, and a smooth robust nonlinear feedback compensator. According to Lyapunov stability analysis, it is proved that the proposed method can guarantee both synchronization and position errors converge and asymptotical stability of the system. Compared with conventional non-synchronized PD friction compensation and trajectory tracking control, experimental results demonstrate the proposed control strategy improve the trajectory tracking precision of finger tip in free space.
By translate the information of joint torque sensor into position vector, and a cross-couple synchronized error expression in drive space and master-slave synchronized error expression in joint space are built for HIT/DLR II robot finger. Then a synchronized impedance control approach is present, including feedbacks of synchronous errors and position errors, and a smooth robust nonlinear feedback compensator. According to Lyapunov stability analysis, it is proved that the proposed method can guarantee both synchronization and position errors converge and asymptotical stability of the system. Compared with conventional non-synchronized PID impedance control, experimental results demonstrate the validity of the proposed control strategy. And in interaction of robot finger with a person, it generates compliance and smooth movement according to the joint torque, which demonstrates that the ideal joint impedance performance is successfully achieved. All this will provide a good base of multi-finger grasping manipulation and human-robot coordinating manipulation.
When the dexterous hand works in uncertain environment, the finger may encounter obstacle or disturbance, which may cause release or damage the grasped object. To solve this problem, the synchronized error expression between multiple fingers is built in Cartesian space, and then a synchronized impedance control approach in Cartesian space is present. The main idea is cooperates the undisturbed fingers with the disturbed finger, which keep relative balance of grasping manipulation. According to Lyapunov stability analysis, it is proved that the proposed method can guarantee asymptotical stability of the system. The experimental results demonstrate the proposed control strategy can avoid damaging or releasing the grasping object, and enhance the anti-interference ability of the dexterous robot hand.
引文
1 H. Liu, P. Meusel, Seitz, et al. The Modular Multisensory DLR-HIT-Hand. Mechanism and Machine Theory. 2007, (42):612~625
2姜力.具有力感知功能的机器人灵巧手手指及控制的研究.哈尔滨工业大学博士论文. 2001:1~2
3张立彬,杨庆华,胥芳,等.机器人多指灵巧手及其驱动系统研究的现状.农业工程学报. 2004:273~274
4 Y. Nakano, M. Fujie, Y. Hosada. Hitachi’s Robot Hand. Robotics Age. 1984, 6(7):18~20
5 S. C. Jacobsen, J. E. Wood, D. F. Knutti, et al. The UTAH/MIT Dextrous Hand: Work in Progress. The International Journal of Robotics Research. 1984, 3(4):21~50
6 Shadow Robot Company. Shadow Dexterous Hand C5 Technical Specification. (2006-11-08). http://www.shadowrobot.com/downloads/shadow_dextrous_hand_ tech-nical_specification_C5.pdf
7 L. R. Lin, H. P. Huang. NTU Hand: A New Design of Dexterous Hands. Journal of mechanical design. 1998, 120(2):282~292
8 L. R. Lin, H. P. Huang. DSP-Based Fuzzy Control of A Multifingered Robot Hand Systems. Proceedings of the IEEE International Conference on Intelligent Systems for the 21st Century. Vancouver, BC, Canada. 1995:3672~3677
9 C. Lovchik, H. Aldridge, M. Diftler. Design of the NASA Robonaut Hand. Proc.ASME Dynamics and Control Division, Soc. of Mechanical Engineers, New York, 1999:813~830
10 M. Diftler. Evolution of the NASA-DARPA Robonaut control system. Proceedings of the 2003 IEEE International Conference on Robotics & Automation. Taibei, Taiwan, 2003:2543~2548
11 H. Liu, J. Butterfass, S. Knoch, et al. A New Control Strategy for DLR’s Multisensory Articulated Hand. IEEE Control Systems. 1999, 19(2):47~54
12 Butterfass, G. Hirzinger, S. Knoch, et al. DLR’s Multisensory Articulated Hand, Part I: Hard and Software Architecture. Proceedings of IEEE International Conference on Robotics and Automation. 1999:2081~2086
13 U. Rembold. The Karlsruhe Dextrous Hand I and II. Proceedings of the IEEE International Conference on Robotics and Automation. Detroit, Tokyo. 1999:101~110
14 H. Kawasaki, T. Komatsu, K. Uchiyama. Dexterous Anthropomorphic Robot Hand with Distributed Tactile Sensor: Gifu Hand II. IEEE/ASME Transactions on Mechatronics. 2002, 7(3):296~303
15 T. Mouri, H. Kawasaki, K. Yoshikawa, et al. Anthropomorphic Robot Hand: Gifu Hand III. ICCAS, 2002:1288~1293
16 F. Lotti, P. Tiezzi, G. Vassura. Development of UB Hand 3: Early Results. Proceedings of the 2005 IEEE International Conference on Robotics and Automation Barcelona, Spain, April 2005:4499~4504
17 L. Biagiotti, F. Lotti, C. Melchiorri, et al. UBH3: An Anthropomorphic Hand with Simplied Endo-Skeletal Structureand Soft Continuous Fingerpads. In Proc. IEEE Int. Conf. on Roboticsand Automation, 2004, 11(4):4736~4741
18 Y. Zhang, Z. Han, H. Zhang, et al. Design and Control of the BUAA Four-Fingered Hand. Proc. of IEEE Int. Conf. on Robotics and Automation, 2001:2517~2522
19 P. He, M.H. Jin, L. Yang, et al. High Performance DSP/FPGA Controller for Implementation of HIT/DLR Dexterous Robot Hand, Proceedings of the 2004 IEEE International Conference on Robotics and Automation, 2004:2134~2139
20刘增辉,赖英旭.位置传感技术研究进展.传感器技术. 2005, 24(10):5~7
21王之芳.传感器应用技术.西北工业大学出版社. 1996:91~94
22张珂,杨其华,李冰,等.基于霍尔器件的非接触式角度传感器研制.传感技术学报. 2008, 21(6):981~986
23张清,李欣,王清江,等.新型巨磁阻抗传感器的特性研究.传感技术学报. 2007, 20(3):578~581
24 W. Dexin, W. Dexin, et al. 360°Angle Sensor Using Spin Valve Materials with SAF Structure. IEEE Transactions on Magnetics. 2005, 41(10): 3700~3702
25 G. Rieger, K. Ludwig, et al. GMR Sensors for Contactless Position Detection. Sensors and Actuators A: Physical. 2001, 91(1-2):7~11
26 C. P. O. Treutler. Magnetic sensors for automotive applications. Sensors and Actuators A: Physical. 2001, 91(1-2): 2~6
27吴刚,李一博,胡晓莉,等.磁阻传感器在“管道机器人”的地面标记器中的应用.仪器仪表学报. 2004, 25(4):129~135
28 NVE Corporation. Datasheet of the Magnetic Sensor AAV001-11 from NVE Corporation, http://www.nve.com/Downloads/catalog.pdf, Cited 25 Sep 2008
29 C. Taylor, R. Schwarz. The Anatomy of Mechanics of the Human Hand. ArtificialLimbs. 1955, 2:22~35
30 M. Jeannerod. The Formation of Finger Grip During Prehension: A Cortically Mediated Visuomotor Pattern. Behavioural and Brain Research. 1986, (19): 99~116
31 J. R. Napier. The Prehensile Movements of the Human Hand. Journal of Bone and Joint Surgery. 1956, 38B(4): 902~913
32 M. Cutkosky, P. Wright. Modeling Manufacturing Grips and Correlations with the Design of Robotic Hands. Proceedings of the IEEE Conference on Robotics and Automation. 1987: 1533~1539
33 D. M. Lyons. A Simple Set of Grasps for A Dextrous Hand. Proceedings of the IEEE Conference on Robotics and Automation. 1985: 588~593
34 T. Iberall. The Nature of Human Prehension: Three Dextrous Hands in One. Proceedings of the IEEE Conference on Robotics and Automation, 1987: 396~401
35李家炜,刘宏,蔡鹤皋.多指机器人手协调控制研究进展.机器人. 2000,
22(4):023~623
36 R. M. Marry. Control Primitive for Robot Systems. IEEE Trans. On Sys. Man. Cyb. 1992, 22(1):183~193
37 K. S. Fu, R. C. Gonzalez, C. S. G. Lee. Robotics: Control, Sensing, Vision, and Intelligence. McGraw-Hill Book Company, 1987:149~200
38 C. Q. Huang, X. F. Peng, et al. Robust Nonlinear PID Controllers for Anti-windup Design of Robot Manipulators with an Uncertain Jacobian Matrix. Acta Automatica Sinica. 2008, 34(9): 1113~1121
39 P. Herman. Strict Lyapunov Function for Sliding Mode Control of Manipulator Using Quasi Velocities. Mechanics Research Communications. 2009, 36(2): 169~174
40 Z. Sun, R. Xing, et al. Fuzzy Auto-Tuning PID Control of Multiple Joint Robot Driven By Ultrasonic Motors. Ultrasonics. 2009, 46(4): 303~312
41 N.C. Shieh, C.T. Chang, et al. Robust Position Control of A Transportation Carriage Directly Driven By Linear Motor Using Wavelet Neural. Engineering Applications of Artificial Intelligence. 2002, 15(5): 479~489
42 D.E. Whitney,J.L. Nevins. What is the Remote Center Compliance (RCC) and What Can It Do. Robot Sensor, Tactile and Non-Vision. IFS Publication Ltd.1986, 2:135~152
43刘伊威. DLR/HIT仿人灵巧手系统及手指柔顺控制的研究.哈尔滨工业大学工学博士论文. 2006, 12:17~18
44殷跃红,尉忠信,朱剑英.机器人柔顺控制研究. 1998, 20(3): 232~240
45 M.T. Mason. Compliance and Force Control for Computer Controlled Manipulators. IEEE Trans. Syst. Man. Cybern. 1981, 11(6):418~432
46 M. H. Raibert, J. J. Craig. Hybrid Position/Force Control of Manipulators. Transactions of the ASME Journal of Dynamic Systems, Measurement, and Control. 1981, 102:126~133
47 G. Ferretti, G.Magnani, P. Rocco. Towards the Implementation of Hybrid Force/Position Control in Industrial Robots. IEEE Transactions on Robotics and Automation, 1997, 13(6):838~845
48 Y. Karayiannidis, G. Rovithakis, Z. Doulgeri. Force/Position Tracking for A Robotic Manipulator in Compliant Contact with A Surface Using Neuro-Adaptive Control. Automatica. 2007, (43):1281 ~1288
49 M. Farooq, D. B. Wang. Hybrid Force/Position Control Scheme for Flexible Joint Robot with Friction Between and the End-Effector and the Environment. International Journal of Engineering Science. 2008, 46(12):1266~1278
50 C.H. An, J.M. Hollerbach. The Role of Dynamic Models in Cartesian Force Control of Manipulators. International Journal of Robotics Research. 1989, 8(4):51~72
51 N.Hogan. Impedance Control: An Approach to Manipulator: Part I,II,and III. Transactions of the ASME Journal of Dynamic Systems, Measurement, and Control. 1985, (107):1~24
52刘宏.机器人宏/微操作器系统的研究.哈尔滨工业大学博士学位论文. 1993:126~130
53 D. Lawrence. Impedance Control Stability Properties in Common Implementations. Proceedings of the IEEE International Conference on Robotics and Automation. 1988:1185~1192
54 G. Morel, P. Bidaud. A Reactive External Force Loop Approach to Control Manipulators in the Presence of Environmental Disturbances. Proceedings of the IEEE International Conference on Robotics and Automation. 1996:1229~1234
55 G.Morel, E.Malis, S.Boudet. Impedance Based Combination of Visual and Force Control. Proceedings of the IEEE International Conference on Robotics and Automation. Leuven, Belgium. 1998:1743~1748
56 T. A. Lasky, T. C. Hsia. On Force-tracking Impedance Control of Robot Manipulators. Proc. IEEE Int. Conf Robot and Automat. Sacramento, California-April, 1991:274~280
57 J. K. Salisbury. Active Stiffness Control of a Manipulator in CartesianCoordinates. Proc 19th IEEE Conf Decision Contr. 1980: 95~100
58 S. P. Chan, B. Yao, et al. Robust Impedance Control of Robot Manipulators. Int. J Robotice Automation. 1991, 6(4): 220~227
59 H. Seraji, R. Colbaugh. Force Tracking in Impedance Control. The International Journal of Robotics Research. 1997, 16(1):97~117
60李杰,韦庆,常文森,等.基于阻抗的自适应力跟踪方法.机器人. 1999, 21(1):23~29
61 J. Fax, R. M. Murray. Information Flow and Cooperative Control of Vehicle Formations. IEEE Transactions on Automatic Control. 2004, 49(9): 1465~1476
62 R. Sepulchre, D. Paley, Leonard, et al. Stabilization of Planar Collective Motion with Limited Communication. IEEE Transactions on Automatic Control. 2008, 53(3):706~719
63 J. Fax, M. R. Murray. Information Flow and Cooperative Control of Vehicle Formations. IEEE Transactions on Automatic Control. 2004, 49(9):1465~1476
64 L. Scardovi, A. Sarlette, R. Sepulchre. Synchronization and Balancing on the N-Torus. Systems and Control Letters. 2007. 56(5):335~341
65 C. O. Alford, Belyeu. Coordinated Control of Two Robot Arms. In: Proc. IEEE Int. Conf. Robotics Automation. 1984: 468~473
66 S. Arimoto, F. Miyazaki, S. Kavamura. Cooperative Motion Control of Multi-Robot Arms Or Fingers. In: Proc. IEEE Int. Conf. Robotics Automation, 1987: 1407~1412
67 T. E. Alberts, D. I. Soloway. Force Control of A Multi-Arm Robot System. IEEE International Conference on Robotics and Automation, 1988:1490~1496
68 Y. Nakamura, K. Nagai, T. Yoshikawa. Mechanics of Coordinative Manipulation By Multiple Robotic Mechanisms. In: Proc. IEEE Int. Conf. Robotics Automation, 1987:991~998
69 S. Hayati. Hybrid Position/Force Control of Multi-Arm Cooperating Robots. In: Proc. IEEE Int. Conf. Robotics Automation, San Francisco, CA, 1986:82~89
70 N. Xi, T. J. Tran, A. K. Bejczy. Event-Based Planning and Control for Multi-Robot Coordination. In: Proc. IEEE Int. Conf. Robotics Automation, Atlanta, GA, 1993:251~257
71 M. Kumar, D.P. Garg. Sensor-Based Estimation and Control of Forces and Moments in Multiple Cooperative Robots. Journal of Dynamic Systems, Measurement, and Control. 2004:276~283
72 K. K. Ahn, H. T. C. Nguyen. Intelligent Switching Control of A Pneumatic Muscle Robot Arm Using Learning Vector Quantization Neural Network.Mechatronics. 2007, 17(4-5): 255~262
73 I. I. Blekhman, P.S. Landa, M.G Rosenblum. Synchronization and Chaotization in Interacting Dynamical Systems. ASME Appl. Mech. Rev. 1995, 48 (11):733~752
74 H. Nijmeijer. A Dynamical Control View on Synchronization. Phys.D, 2001, (154):219~228
75 Z. Hongfu. Architecture on Clamping Motors Synchronized Controller in Injection Mould machine. IEEE International Conference on Control and Automation. Guangzhou, China, 2007: 2178~2182
76 P. Perez, C. Nunez, et al. Comparison of Multi-Motor Synchronization Techniques. The 30th Annual Conference of IEEE on Industrial Electronics Society. Busan, Korea, 2004:1670~1675
77 Y. Koren. Cross-Coupled Biaxial Computer Controls for Manufacturing Systems, ASME Journal of Dynamic Systems, Measurement, and Control. 1980, 102(2):256~272
78 M. Tomizuka, J.S. Hu, T.C. Chiu, et al. Synchronisation of Two Motion Conbol Axes Under Adaptive Feedforward Control. Trans. ASME J. Dyn. Means. Control. 1992, (114):196~203
79孙金凤.基于同步控制的多指手操作控制方法的研究.哈尔滨工业大学工学硕士论文. 2008, 06:7~9
80 S. J. Huang, C. C. Chen. Application of Self-Tuning Feed-Forward and Cross-Coupling Control in A Retrofitted Milling Machine. International Journal of Machine Tools and Manufacture. 1995, 35(4):577~591
81 Q. Han, Q. Guo. Cooperatingly Synchronized Control for 6-DOF Virtual-Axis Machine Tool. The 7th International Workshop on Advanced Motion Control. Maribor, Slovenia, 2002:171~175
82 Y. Dongmei, G. Qingding, et al. Position Synchronized Control of Dual Linear Motors Servo System Using Fuzzy Logic. Proceedings of the 6th World Congress on Intelligent Control and Automation. Dalian, China, 2006: 8041~8044
83 Y. Xiao, K. Y. Zhu. Optimal Synchronization Control of High-Precision Motion Systems. IEEE Transactions on Industrial Electronics. 2006, 53(4):1160~1169
84 D. Zhao, S. Li, et al. Robust Adaptive Terminal Sliding Mode-Based Synchronised Position Control for Multiple Motion Axes Systems. Control Theory & Applications. 2009, IET 3(1): 136~150
85 L. Feng, Y. Koren, J. Borenstein. Cross–Couplingmotion Controller for Mobile Robots. IEEE Control Sysems Magazine. 1993, 13(6):35~43
86 D. Sun, G. Feng, C. M. Lam, et al. Orientation Control of A Differential MobileRobot Through Wheels’Synchronization. IEEE/ASME Transactions on Mechatronics. 2005, 10(3):345~351
87 D. Sun and C. Wang. Controlling Swarms of Mobile Robots for Switching Between Formations Using Synchronization Concept. In Proc. IEEE Int. Conf. Robot. Autom. Rome, Italy, 2007:2300~2305
88 L. Ren, J. K. Mills, D. Sun. Adaptive Synchronized Control for A Planar Parallel Manipulator: Theory and Experiments. ASME J. Dyn. Syst., Meas., Control. 2006, 128(4): 976~979
89 D. Sun. Synchronous Tracking Control of Parallel Manipulators Using Cross-coupling Approach. The International Journal of Robotics Research, 2006, 25(11): 1137~1147
90 Shang Weiwei, C. Shuang, et al. Active Joint Synchronization Control for a 2-DOF Redundantly Actuated Parallel Manipulator. IEEE Transactions on Control Systems Technology, 2009, 17(2): 416~423
91 D. Sun, J. K. Mills. Adaptive Synchronized Control for Coordination of Multirobot Assembly Tasks. IEEE Transactions on Robotics and Automation. 2002, 18:498~510
92 A. Rodriguez Angeles, H. Nijmeijer. Mutual Synchronization of Robots Via Estimated State Feedback: A Cooperative Approach. IEEE Trans. Contr. Syst. Technol. 2004, 12(4): 542~554
93 S. Chung, I. Member, J. J. Slotine. Cooperative Robot Control and Concurrent Synchronization of Lagrangian Systems. 2009, 25(3):1~15
94 J. Erdong, S. Zhaowei. Robust Attitude Synchronisation Controllers Design for Spacecraft Formation. Control Theory & Applications. 2009, IET 3(3):325~339
95 J. Shan. Six-Degree-of-Freedom Synchronised Adaptive Learning Control for Spacecraft Formation Flying. Control Theory & Applications, 2008, IET 2(10): 930~949
96 L. Xiaodong, L. Changchun, et al. Synchronization Control Study for Two Cylinders Electro-hydraulic Grasping System. International Conference on Mechatronics and Automation, Harbin, China, 2007: 1650~1654
97 Y. Zhou, S. Liu, et al. On Synchronization Control Strategy of Large Scale Water Press’S Unloading Procedure. Proceedings of the 27th Chinese Control Conference Kunming,Yunnan. China, 2008: 239~242
98 Z. Huaixiang, Y. Kui, et al. Fuzzy Logic Cross-coupling Control of Wheeled Mobile Robots. Proceedings of the 2006 IEEE International Conference on Mechatronics and Automation. Luoyang, China, 2006: 740~744
99 M. Rong, W. Qing xian, et al. Synchronization Controller Design for Uncertain Chaotic Systems Using Disturbance Observer. Control and Decision Conference. Chinese, 2008: 3001~3004
100 A. Rodríguez, J. DeLeón, L. Fridman. Quasi-Continuous High-Order Sliding-Mode Controllers for Reduced-Order Chaos Synchronization. International Journal of Non-Linear Mechanics. 2008, 43(9): 948~961
101 Z. Linhua, Y. Zhichun. A Novel Chaos Control Scheme with Optimality. Proceedings of the 7th World Congress on Intelligent Control and Automation. Chongqing, China, 2008: 4693~4696
102 W. H. Chen, W. X. Zheng. Robust Stability and H∞-Control of Uncertain Impulsive Systems with Time-Delay. Automatica. 2009, 45(1): 109~117
103 Y.W. Liu, M.H. Jin, R. Wei, et al. Embedded FPGA-based Control of the HIT/DLR Hand. Proceedings of the 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics Monterey. California, USA, 2005 :582~587
104张卫宁. TM S320C28x系列DSP的CPU与外设.北京:清华大学出版社, 2004: 305~ 310
105敖银辉.基于DSP的无刷直流电机控制系统研究.广东工业大学学报, 2004, 21(4): 5~9
106李玉山,来新泉,等.电子系统集成设计技术.北京:电子工业出版社,2002
107 MAXIN. 3.3V, High-Speed, RS-485/RS-422 Transceiver in SOT Package. March , 2007
108 TI. TMS320x281x, 280x Serial Communications Interface (SCI) Reference Guide. November, 2004
109何希才.传感器及其应用.国防工业出版社, 2001:95~104
110 R. S. POPOVIC, J. A. FLANAGAN. Sensors Microsystems. Proceedings of 20th International Conference on Microelectronics, NiL, 1995,(2):531~537
111 W. Granig, C. Kolle, Dirk, et al. Integrated Gigant Magnetic Resistance based Angle Sensor, in: IEEE SENSORS 2006. EXCO, Daegu, Korea, 2006:542~545
112 G. Binasch, P. Grünberg, F. Saurenbach et al. Enhanced Magnetoresistance in Layered Magnetic Structures with Antiferromagnetic Interlayer Exchange. Phys. Rev. B. 1989, (39):4828 ~ 4830
113 T Kefalas, G Kalokiris, A Kladas, et al. Design of Skewed Mounted Permanent Magnet Synchronous Generators Based On 2D and 3D Finite Element Techniques, Journal of Materials Processing Technology. 2005, (161):288~293
114 Lu Ren, James K. Mills, Sun Dong. Convex Synchronized Control for a 3-DOFPlanar Parallel Manipulator. Proceedings of the 2006 IEEE International Conference on Robotics and Automation. Orlando, Florida, 2006:1129~1134
115 D. Sun. Position Synchronization of Multiple Motion Axes with Adaptive Coupling Control. Automatica. 2003, 39(6): 997~1005
116 G. Song, L. Cai, Y. Wang. Robust Friction Compensation for Precise and Smooth Position Regulation. Proceedings of the I MECHE Part I Journal of Systems and Control Engineering. 1995, 21(3): 157~161
117 Jiang Li, Liu Hong. Autonomous control of Multi-fingered Hand. Progress in Natural Science, 2006, 16(5): 531~537
118 Jiang Li, Sun Dong. Liu Hong, et al. Study on Inverse Kinematics and Trajectory Tracking Control of Humanoid Robot Finger with Nonlinearly Coupled Joints. Proceedings of the 2007 IEEE International Conference on Mechatronics and Automation. Harbin, China, 2007:3214~3219
119 T. Dzmitry, T. Riichiro, K. Hiroyuki, et al. Intelligent Variable Joint Impedance Control and Development of a New Whole-Sensitive Anthropomorphic Robot Arm. Proceedings of the 2007 IEEE International Symposium on Computational Intelligence in Robotics and Automation Jacksonville. FL, USA, 2007:338~343
120 J. J. E. Slotine, W. Li. Applied Nonlinear Control. Englewood Cliffs, N.J.: Prentice Hall, USA, 1991
121王滨.机器人臂/手抓取及操作规划的研究.哈尔滨工业大学博士论文. 2007:22~24