拟人机械臂动力学建模与智能控制研究
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摘要
本文对一种6-DOF串并混联拟人机械臂进行了动力学建模和智能控制研究。该机械臂为3-2-1布局形式,肩关节为3-DOF球面并联机构,肘关节为2-DOF并联机构,腕关节为平面四杆机构。
建立了肩关节以动平台姿态角为广义变量的标称动力学方程,设计了无源轨迹跟踪控制器,并对其进行了仿真验证;考虑线性化、密度不均等因素造成的误差,建立了肩关节带参数不确定性的动力学方程,并考虑系统参数不确定性和外界扰动,设计了自适应轨迹跟踪控制器;考虑肩关节重复工作特性,设计了自适应迭代学习控制器,并对其进行了重复轨迹跟踪仿真研究。
采用Lagrange方法建立了前臂的标称动力学模型,并设计了径向基神经网络自适应轨迹跟踪控制器;为了降低对不确定参数分别进行学习时的计算量和满足重复轨迹跟踪要求,设计了集中参数自适应迭代学习控制器,并进行了仿真研究。建立了6-DOF混联拟人臂的动力学模型。考虑其参数不确定性、摩擦及外界干扰等因素,对该系统设计了模糊自适应轨迹跟踪控制器,并对其进行了仿真研究。
提出了伪欠驱动动力学模型的概念和伪欠驱动智能控制策略,并对6-DOF拟人臂进行了伪欠驱动智能控制研究。第一步,通过扩展广义变量,采用Lagrange方法建立拟人肩和前臂以及6-DOF拟人机械臂的伪欠驱动动力学模型。第二步,对6-DOF拟人机械臂的伪欠驱动动力学模型设计了神经网络自适应轨迹跟踪控制器,并进行了仿真研究。该控制器采用神经网络学习算法得到扩展的广义变量,通过自适应算法补偿由学习误差带来的动力学不确定性和摩擦、干扰等因素带来的影响,最终得到理想的轨迹跟踪效果。
研制了6-DOF拟人机械臂控制系统,对肩关节和前臂进行了轨迹跟踪实验研究。对各传感器的检测数据进行了数据采集和曲线绘制,为此机械臂的应用奠定了基础。
The dynamics modeling and intelligent control for a class of 6-DOF hybrid humanoid arm, whose layout is 3-2-1 configuration that the shoulder is 3-DOF spherical parallel mechanism, elbow is 2-DOF parallel mechanism and wrist is planar 4-bar mechanism, are studied.
The nominal dynamics model based on orientation parameters of moving plant of shoulder is developed, the passive trajectory tracking controller is designed and validated by simulation; the dynamics model with parameter uncertainties is ulteriorly developed considering the errors brought by linearization of components, approximately computing in linear density etc., and adaptive trajectory tracking controller is designed considering parameter uncertainties and external disturbances. Considering the characteristic of repeated acting of shoulder, an adaptive ILC (Iterative learning controller) is designed.
The nominal dynamics model of forearm is developed by Lagrange method and RBF (Radial basis function) NN (Neural network) Adaptive trajectory tracking controller is designed. For the reduction of calculation during uncertainty parameters learning and the realization of repeated trajectory tracking, the lumped parameter Adaptive ILC is designed and validated by simulation. The dynamics model of 6-DOF hybrid humanoid mechanism arm is developed. Considering the parameter uncertainties, frictions and external disturbances etc., a Fuzzy Adaptive trajectory tracking controller is designed and validated by simulation.
Pseudo underactuated dynamics model and Pseudo underactuated intelligent control strategy are proposed, and the study of pseudo underactuated intelligent control for 6-DOF humanoid arm is done. The first step, the pseudo underactuated dynamics models of shoulder, humanoid forearm and 6-DOF humanoid mechanism arm is developed by Lagrange method and extending general variable. The second step, A NN Adaptive trajectory tracking controller is designed for the pseudo underactuated dynamics model of 6-DOF humanoid mechanism arm, and the feasibility of this controller is validated by simulation. The extended general variables is learned by NN algorithm, and the dynamics uncertainty induced by learning errors and the influences induced by frictions and disturbances are compensated by adaptive algorithm. The perfect tracking results are gained.
The control system of 6-DOF hybrid humanoid mechanism arm is researched and manufacture. The trajectory tracking experiments of shoulder and forearm, which establishes the foundation of application, are done and the dates detected by sensors are gathered and plotted.
建立了肩关节以动平台姿态角为广义变量的标称动力学方程,设计了无源轨迹跟踪控制器,并对其进行了仿真验证;考虑线性化、密度不均等因素造成的误差,建立了肩关节带参数不确定性的动力学方程,并考虑系统参数不确定性和外界扰动,设计了自适应轨迹跟踪控制器;考虑肩关节重复工作特性,设计了自适应迭代学习控制器,并对其进行了重复轨迹跟踪仿真研究。
采用Lagrange方法建立了前臂的标称动力学模型,并设计了径向基神经网络自适应轨迹跟踪控制器;为了降低对不确定参数分别进行学习时的计算量和满足重复轨迹跟踪要求,设计了集中参数自适应迭代学习控制器,并进行了仿真研究。建立了6-DOF混联拟人臂的动力学模型。考虑其参数不确定性、摩擦及外界干扰等因素,对该系统设计了模糊自适应轨迹跟踪控制器,并对其进行了仿真研究。
提出了伪欠驱动动力学模型的概念和伪欠驱动智能控制策略,并对6-DOF拟人臂进行了伪欠驱动智能控制研究。第一步,通过扩展广义变量,采用Lagrange方法建立拟人肩和前臂以及6-DOF拟人机械臂的伪欠驱动动力学模型。第二步,对6-DOF拟人机械臂的伪欠驱动动力学模型设计了神经网络自适应轨迹跟踪控制器,并进行了仿真研究。该控制器采用神经网络学习算法得到扩展的广义变量,通过自适应算法补偿由学习误差带来的动力学不确定性和摩擦、干扰等因素带来的影响,最终得到理想的轨迹跟踪效果。
研制了6-DOF拟人机械臂控制系统,对肩关节和前臂进行了轨迹跟踪实验研究。对各传感器的检测数据进行了数据采集和曲线绘制,为此机械臂的应用奠定了基础。
The dynamics modeling and intelligent control for a class of 6-DOF hybrid humanoid arm, whose layout is 3-2-1 configuration that the shoulder is 3-DOF spherical parallel mechanism, elbow is 2-DOF parallel mechanism and wrist is planar 4-bar mechanism, are studied.
The nominal dynamics model based on orientation parameters of moving plant of shoulder is developed, the passive trajectory tracking controller is designed and validated by simulation; the dynamics model with parameter uncertainties is ulteriorly developed considering the errors brought by linearization of components, approximately computing in linear density etc., and adaptive trajectory tracking controller is designed considering parameter uncertainties and external disturbances. Considering the characteristic of repeated acting of shoulder, an adaptive ILC (Iterative learning controller) is designed.
The nominal dynamics model of forearm is developed by Lagrange method and RBF (Radial basis function) NN (Neural network) Adaptive trajectory tracking controller is designed. For the reduction of calculation during uncertainty parameters learning and the realization of repeated trajectory tracking, the lumped parameter Adaptive ILC is designed and validated by simulation. The dynamics model of 6-DOF hybrid humanoid mechanism arm is developed. Considering the parameter uncertainties, frictions and external disturbances etc., a Fuzzy Adaptive trajectory tracking controller is designed and validated by simulation.
Pseudo underactuated dynamics model and Pseudo underactuated intelligent control strategy are proposed, and the study of pseudo underactuated intelligent control for 6-DOF humanoid arm is done. The first step, the pseudo underactuated dynamics models of shoulder, humanoid forearm and 6-DOF humanoid mechanism arm is developed by Lagrange method and extending general variable. The second step, A NN Adaptive trajectory tracking controller is designed for the pseudo underactuated dynamics model of 6-DOF humanoid mechanism arm, and the feasibility of this controller is validated by simulation. The extended general variables is learned by NN algorithm, and the dynamics uncertainty induced by learning errors and the influences induced by frictions and disturbances are compensated by adaptive algorithm. The perfect tracking results are gained.
The control system of 6-DOF hybrid humanoid mechanism arm is researched and manufacture. The trajectory tracking experiments of shoulder and forearm, which establishes the foundation of application, are done and the dates detected by sensors are gathered and plotted.
引文
1于秀丽,魏世民,廖启征.仿人机器人发展及其技术探索.机械工程学报, 2009, 45(3):71-75
2周玉林,高峰.仿人机器人构型.机械工程学报, 2006, 42(11): 66-74
3刘杰,张玉茹.机器人灵巧手抓持分类器的设计与实现.机器人, 2003, 25(3): 259-263
4彭光正,余麟,刘昊.气动人工肌肉驱动仿人灵巧手的结构设计.北京理工大学学报, 2006, 7: 593-597
5邹海荣,龚振邦,罗均.仿生眼的研究现状与发展趋势.机器人, 2005, 27(05): 470-474
6金振林,曹舜,高峰.新型机器人肩关节及其运动学分析.中国机械工程, 2009, 20(14): 1639-1642
7范顺成,韩书葵,谷慧茹.两足步行机器人并联腿机构的稳定性分析.河北工业大学学报, 2004, 33(1): 27-31
8潘智昊,谢少荣,罗均,等.仿生双目异向运动控制系统.制造业自动化, 2009, 31(1): 34-37
9刘伟,齐晓慧.基于视觉的机械手臂自主抓物的实现.自动测量与控制, 2008, 27(12): 79-80
10辛菁,刘丁,杨延西.基于图像的机器人视觉伺服免疫控制.仪器仪表学报, 2008, 29 (11): 2253-2259
11石玉秋,孙炜,孙洪淋.基于小波网络的机器人视觉伺服控制研究.微计算机信息, 2007, 23(7-2): 214-216
12陈辉,宋爱国,金世俊.带有力觉和触觉临场感的灵巧手主从系统的设计.机器人, 1998, 20(6): 438-448
13单保祥,王琪民,杨浩涌.微型触觉传感器敏感单元的分析和测试.中国科学技术大学学报, 1999, 29(4): 415-420
14胡军,李嘉,刘文江,等.基于CMAC的触觉传感信号自适应逆滤波器设计.微电子学与计算机, 2003, 8: 62-65
15黄英,明小慧,向蓓. A New Design of Flexible Three-Dimension Force Tactile Sensor of Robot.传感技术学报, 2008, 21(10): 1696-1699
16刘清君,许改霞,徐莹.仿生嗅觉神经芯片的研究进展.国外医学生物医学工程分册, 2005, 28(1): 56-61
17庄哲民,黄惟一.机器人人工嗅觉系统设计.东南大学学报, 2004, 34(1): 28-31
18李界家,吴成东,朱栋华.基于神经网络的人工嗅觉系统设计.自动化仪表, 2003, 24(4): 17-19
19窦振中.模糊逻辑控制技术及其应用(第1版).北京:北京航空航天大学出版社, 1995: 1-33
20赵林明,胡浩云,魏德华,等著.多层前向人工神经网络.郑州:黄河水利出版社, 1999: 1-7
21丁希仑,李海涛,解玉文.基于Internet的拟人双臂机器人遥操作系统的研究.高技术通讯, 2006, 16(8): 808-812
22吴伟国,李小宁,王瑜.类人机器人腰部关节平衡作用研究与仿真.机械设计与制造, 2006, 5: 112-114
23杨玉贵,彭光正,王毅枫.气动人工肌肉驱动的双臂机器人及其协调控制研究进展.机床与液压, 2008, 36(4): 181-184
24 Chang W. C., Lee S. A.. Autonomous vision-based pose control of mobile robots with tele-supervision. Proc of the IEEE International Conf on Control Applications. Piscataway, NJ, USA: IEEE, 2004: 1049-1054
25 Marchand E., Chaumette F.. Feature tracking for visual servoingpurposes. Robotics and Autonomous Systems, 2005, 52(1): 53-70
26 Edward G.Freedman. Interactions between eye and head control signals can account for movement kinematics. Biological Cybernetics, 2001, 84(6): 453-462.
27 http://tech.sina.com.cn/ology/2000-06-10/27785.shtml
28李贻斌.现代科技革命与机器人的发展.山东交通学院学报, 2002, 10(4): 53-74
29李艳杰,徐继宁,王侃.仿人机器人发展现状及其腰关节的作用.沈阳工业学院学报, 2004, 23(1): 18-23
30张炜,美浓地池一.从日本机器人技术的现状看机器人技术产业化发展.机器人技术与应用, 2006, 3: 1-5
31柯显信.仿人形机器人双足动态步行研究. [上海大学博士学位论文]. 2005: 1-10
32刘英卓.拟人形机器人建模、控制与协调研究. [中国科学院沈阳自动化研究所博士学位论文]. 2003: 1-21
33 J. Butterfab, M. Grebenstein, H. Liu, et al. DLR-Hand II: Next Generation of Adextrous Robot Hand. IEEE International Conference on Robotics and Automation, Seoul, Korea,2001:109-114
34冯金光,周华平,马宏绪.基于DSP的仿人机器人运动控制器设计.工业仪表与自动化装置, 2005, 2: 67-69
35杨庆,马宏绪. CMAC在仿人机器人逆运动学计算中的应用.机器人技术, 2006, 22(3-2): 187-208
36朱志斌,王岩,陈兴林.一种双足机器人实时步态规划方法及相关数值算法.机器人, 2008, 30(6): 521-527
37刘伊威,金明河. D LR/HIT仿人机器人灵巧手的设计.机械制造, 2006, 44(507): 32-35
38赵大威,姜力,金明河,等.仿人型机器人手的力矩保持功能及控制系统.电机与控制学报, 2007, 11(5): 497-501
39吴伟国,宋策,孟庆梅.仿人头像机器人“H&Frobot-Ш”语音及口形系统研制与实验.机械设计, 2008, 25(1): 15-19
40刘江华,程君实,弥佳品.基于视觉的动态手势识别及其在仿人机器人交互中的应用.机器人, 2002, 24(3): 197-216
41姜山,程君实,陈佳品,等.基于多目标遗传算法的仿人机器人中枢神经运动控制器的设计.机器人, 2001, 23(1): 58-67
42彭娟春,顾立忠,苏剑波.基于Camshift和Kalman滤波的仿人机器人手势跟踪.上海交通大学学报, 2006, 40(7): 1162-1165
43余蕾斌,曹其新,孙毅军.基于压应力中心的仿人机器人离散轨迹运动控制.上海交通大学学报. 2007, 41(8): 1263-1266
44陈健,雷旭升,苏剑波.基于智能体的仿人机器人分层控制系统.高技术通讯, 2007, 17(6): 586-590
45唐粲,贠超,刘达. CT导航微创外科混联机器人拓扑结构分析.机器人, 2008, 30(2):107-111
46 Elif Deryaübeyli. Implementing eigenvector methods/probabilistic neural networks for analysis of EEG signals. Neural Networks, 2008, 21(9): 1410-1417
47 Olivia Mendoza, Patricia Melin, Guillermo Licea. A hybrid approach for image recognition combining type-2 fuzzy logic, modular neural networks and the Sugeno integral. Information Sciences, 2009, 179(13): 2078-2101
48 Lisheng Xu, Max Q. H., Meng, Kuanquan Wang. Pulse images recognition using fuzzy neural network. Expert Systems with Applications, 2009, 36(2): 3805-3811
49 Monica Bianchini, Marco Maggini, Lorenzo Sarti. Recursive Neural Networks and Their Applications to Image Processing. Advances in Imaging and Electron Physics, 2006, 140: 1-60
50 Ren Shuyan Pu Zhaobang Zhuang Zhitao. Image filter arithmetic based on fuzzy neural network .Chinese Journal of Scientific Instrument, 2006, (S1): 4
51王秀英.基于BP神经网络的故障模式识别与应用.机电工程技术, 2008, 37(10): 103-118
52 Karayiannis N. B., Xiong Y. H.. Training reformulated radial basisfunction neural networks capable of identifying uncertainty in data clas-sification. Proc. of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. 2005: 1-8
53 R. Srinivasan, C. Wang, W. K. Ho, etc.. Context-based recognition of process states using neural networks .Chemical Engineering Science, 2005, 60(4): 935-949
54王丹凤,李书臣,翟春艳.基于神经网络参数优化的迭代学习控制算法.河南科技大学学报(自然科学版), 2008, 29(6): 42-44
55 Mehdi Ghatee, Ali Mohades. Motion planning in order to optimize the length and clearance applying a Hopfield neural network. Expert Systems with Applications, 2009, 36(3): 4688-4695
56 Erick CantúPaz, Chandrika Kamath. Evolving neural networks to identify bent-double galaxies in the FIRST survey. Neural Networks, 2003, 16(3-4): 507-517
57焦李成.神经网络的应用与实现.西安:西安电子科技大学出版社, 1991: 1-30
58 Y. P. Chu, C. M. Hsieh. An artificial neural network model with modified perceptron algorithm. Parallel Computing, 1992, 18(9): 983-996
59 Hopfield J J.. Neural Networks and Physical Systems with Emergent Collective Computational Abilities. Proc of the National Academy of Sciences of the United States of America, 1982, 79(8): 2554-2558
60胡守仁.神经网络导论.长沙:国防科技大学出版社, 1993: 1-55
61 J. J. Zhu, W. P. Xiao. Intelligent control of time-varying dynamical systems using CMAC artificial neural network. Mathematical and Computer Modelling, 1995, 21(1-2): 89-107
62 Juan Ignacio, Mulero-Martínez. Analysis of the errors in the modelling of manipulators with Gaussian RBF neural networks. Neurocomputing, 2009, 72(7-9): 1969-1978
63芮执元,孙雪莲,剡昌锋.基于模糊神经网络的蛇型机器人的智能控制.航空制造技术, 2005, 1: 71-74
64 T. Chatchanayuenyong, M. Parnichkun. Neural network based-time optimal sliding mode control for an autonomous underwater robot. Mechatronics, 2006, 16(8): 471-478
65高建树,邢志伟,张宏波.基于观测器的水下机器人神经网络自适应控制.机器人, 2004,26(6): 515-518
66昝鹏,颜国正,于莲芝.基于神经网络PID控制的柔性微机器人系统.机器人, 2007, 29(3): 219-229
67 Dai bing Zhang, De wen Hu, Lin-cheng Shen. A Bionic Neural Network for Fish-Robot Locomotion. Journal of Bionic Engineering, 2006, 3(4): 187-194
68王洪斌,李铁龙,郭继丽.机器人的神经网络鲁棒轨迹跟踪控制.电机与控制学报, 2005, 9(2): 145-150
69 Masanori Sato, Atushi Kanda, Kazuo Ishii. Adaptive control of nonlinear PID-based analog neural networks for a nonholonomic mobile robot. Neurocomputing, 2008, 71(7-9): 1561-1565
70 ?ahin Yildirim. Design of a proposed neural network control system for trajectory controlling of walking robots. Simulation Modelling Practice and Theory, 2008, 16(3): 368-378
71 Christophe Sabourin, Olivier Bruneau. Robustness of the dynamic walk of a biped robot subjected to disturbing external forces by using CMAC neural networks. Robotics and Autonomous Systems, 2005, 51(2-3): 81-99
72李霞,谢涛,陈维山.基于神经网络的双足机器人逆运动学求解.机械设计, 2003, 20(4): 36-39
73陈华志,谢存禧,曾德怀.基于神经网络的移动机器人路径规划算法的仿真.华南理工大学学报(自然科学版), 2003, 31(6): 56-59
74高峻峣,陆际联.轮式机器人遗传模糊神经网络转向控制.北京理工大学学报, 2003, 23(2): 176-180
75柳玉甜,蒋静坪.基于多模型和小脑模型关节控制器神经网络的移动机器人故障诊断.电工技术学报, 2007, 22(3): 153-158
76 L. A. Zadeh. Fuzzy sets. Information and Control, 1965, 8:338-353
77 K. Tanaka and M. Sugeno. Stability analysis and design of fuzzy control systems. Fuzzy Sets Syst., 1992, 45: 135-156
78 T. Takagi and M. Sugeno. Fuzzy identification of systems and its pplications to modeling and control. IEEE Trans. Syst. Man Cybern, 1985, 15: 116-132
79 L. X. Wang. Adaptive fuzzy systems and control: design and stability analysis. Englewood Cliffs, NJ: Prentice-Hall, 1994
80 E. H. Mamadani. Application of fuzzy alyorithms for simple dynamic plant. Proc. IEE., 1974,121: 1585-1588
81宋永端,高为炳.用于机器人轨迹跟踪的变结构控制.控制理论与应用, 1991,8(1):265-268
82 Y. D. Song. Path Tracking Control of Robot Using Variable Structure Model. Control Theory and Application. Control Theory and Control Application, 1991, 7(1): 201-204
83 C. M. Lin, T. Hiyama. Application of Fuzzy Logic Control to A Manipulator. Robot and Automation, 1991, 7(5): 688-691
84邓辉,孙富春,孙增圻.机械手的模糊逆模型鲁棒控制.自动化学报, 2001, 27(4): 521-530
85陈勇;吕霞付.基于模糊控制的放射性试剂分装机器人,仪器仪表学报, 2009, 30(2): 330-334
86洪昭斌,陈力.漂浮基双臂空间机器人系统的模糊神经网络自学习控制.机器人, 2008, 30(5): 435-439
87 Miller W. T. Real-time neural network control of a bipedwalking robot. IEEE Control Systems Magazine. 1994, 14: 14-48
88方道星,余跃庆,陈炜.基于模糊控制的2R欠驱动机器人位置控制.机械工程学报, 2008, 44(1): 144-154
89 Arimoto S., Kawamura S., M. iyazaki F.. Better operation of robots by learning. Journal of Robotic Systems, 1984, 1(2): 123-140
90 Hyo-Sung Ahn, Kevin L. Moore, YangQuan Chen. Stability analysis of discrete-time iterative learning control systems with interval uncertainty. Automatica, 2007, 43: 892-902
91孙明轩,黄宝健.迭代学习控制.北京:国防工业出版社, 1999: 4-9, 15-20, 73-75
92 Sun M. X., Wang D. W.. Iterative learning control with initial rectifying action. Automatica, 2002, 38(7): 1177-1182
93 Arif M., Ishihara T., Inooka H.. Iterative learning control using information data base. Journal of Intelligent and Robotic Systems, 1999, 25(1): 27-41
94 Tian S. P., Xie S. L., Fu X. L.. Fast algorithm of iterative learning control. Journal of South China University of Technology (Natural Science Edition), 2002, 30(5): 37-40
95张朝霞,王华奎.模糊神经网络及其在信道均衡中的应用.科技情报开发与经, 2005, 15(16): 151-158
96王耀南,孙炜.基于模糊神经网络的机器人自学习控制.电机与控制学报, 2001, 5 (2): 92-102
97白萍,方廷健,葛运健.基于神经网络补偿的机器人稳定自适应控制.模式识别与人工智能, 2001, 14(2): 162-165
98吴成东,武荣文,张俊杰.机器人神经网络控制研究进展.沈阳建筑工程学院学报, 1998, 14(1): 96-100
99金耀初,蒋静坪.一类非线性系统的模糊变结构控制及应用.控制与决策, 1992, 7(1): 36-40
100徐敏,林辉. ILC理论与应用新进展.控制理论与应用, 2003, 22(1): 4-7
101 Choi J., Park H. J.. Use of Networks in Iterative Learning Control Systems. Int. J. Systems Science, 2000, 31(10):1227-1239
102 Xu J., Vigwanathna B., Qu Z.. Robust iterative learning control for a class of nonlinear systems. Automatica, 1998, 34(8): 983-988
103 Xu J., Vigwanathna B.. Adaptive robust learning control with dead zone scheme. Automatica, 2000, 36(1): 91-99
104郭毓,申晓宁,陈庆伟,等.一类高阶线性时变系统自适应迭代学习辨识.兵工学报, 2008, 29(4): 454-458
105李研彪.新型6-DOF串并混联拟人机械臂的性能分析与设计. [燕山大学工学博士学位论文]. 2008: 40, 58-80
106郭祖华,陈五一,陈鼎昌. 6-UPS型并联机构的刚体动力学模型.机械工程学报, 2002, 38(11): 53-57
107 Gosselin C. M.. The optimum design of robotic manipulators using dexterity indices. Journal of Robotics and Autonomous systems, 1993, 9(4): 213-226
108黄田,曾宪菁,曾子平,等.等顶锥角3自由度球面并联机构的全参数解析尺度综合.机械工程学报, 2000, 36(8): 15-19
109 Xin-Jun Liu, Zhen-lin Jin, Feng Gao. Optimum design of 3-DOF spherical parallel manipulators with respect to the conditions and stiffness indices. Mechanism and Machine Theory, 2000, 35: 1257-1267
110高征,高峰.球面3自由度并联机构的正解分析新方法.机械设计与制造, 2006, 9: 122-124
111何开明.基于球面三角学的球面并联机构位姿正解.武汉理工大学学报, 2003, 25(6): 46-48
112张立杰,刘辛军.球面三自由度并联机器人可达工作空间的研究.中国机械工程, 2001, 12(10): 1122-1124
113孙立宁,刘宇,祝宇虹.一种用于腕关节的球面三自由度并联解耦机构位置分析.中国机械工程, 2003, 14(10): 831-833
114李研彪,金振林.球面三自由度机器人的力矩输入均衡性能分析与设计.光学精密工程, 2007, 15(5): 730-734
115赖一楠,张广玉,段志鸣,等.面向控制的3-RRR球面并联机构正运动学实时解法.中国机械工程, 2003, 14(2): 113-115
116许建新,侯忠生.学习控制的现状与展望.自动化学报, 2005, 31(6): 943-955
117代颖.不确定性机器人鲁棒自适应控制方法研究. [西安交通大学博士学位论文]. 1998: 11-32
118 Yiannis Karayiannidis, George Rovithakis, Zoe Dou- lgeri. Force/position tracking for a robotic manipulator in compliant contact with a surface using neuro- adaptive control. Automatica, 2007, 43(7): 1281-1288
119 Luis J. Ricalde, Edgar N. Sanchez. Output tracking with constrained inputs via inverse optimal adaptive recurrent neural control. Engineering Application of Artificial Intelligence, 2008, 21(4): 591-603
120 Fathi Fourati, Mohamed Chtourou, Mohamed Kamoun. Stabilization of unknown nonlinear systems using neural networks. Applied Soft Computing, 2008, 3, 8(2): 1121-1130
121 Montambault S., Gosselin C. M.. Analysis of underactuated mechanical grippers. ASME Journal Of Mechanical Design, 2001,123(3): 367-374
122何广平,陆震,王凤翔.欠驱动冗余度机器人运动优化控制.宇航学报, 2002, 23(5): 16-20
123 A. De Luca, G. Oriolo. Stabilization of the Acrobot via iterative state steering. 1998 IEEE Int. Conf. on Robotics and Automation, 1998: 3581-3587
124 A. De Luca, R. Mattone, G. Oriolo. Stabilization of underactuated robots: Theory and experiments for a planar 2R manipulator. 1997 IEEE Int. Conf. On Robotics and Automation, 1997: 3274-3280
125 Alessandro De Luca, Giuseppe Oriolo. Trajectory Planning and Control for Planar Robots with Passive Last Joint. The International Journal Of Robotics Research, 2002: 575-590
126 Mahmut Reyhanoglu, Arjan vander schaft, N. Harris McClamroch, etc.. Dynamics and Control of a class of underactuateed Mechnical Systems. IEEE Transactions on Automatic Control, 1999, 44(9): 1663-1671
127 M. Bergerman, C. Lee, Y. Xu. A dynamic coupling index for underactuated manipul ators. J. of Robotic Systems, 1995, 12(10): 693-707
128 Y. Liu, Y. Xu, M. Bergerman. Cooperation control of multiple manipulators with passive joints. IEEE Transactions on Robotics and Automation, 1999, 15(2): 258-267
129 Xuzhi LAI, Jin-Hua SHE, Yasuhiro OHYAMA, etc.. A Fuzzy Control Strategy for Acrobots Combining Model-Free and Model-Based Control. IEE Proceedings Control Theory and Applications, 1999, 146(6): 1-17
130 S. H. Collins, M. Wisse, A. Ruina. A three-dimensional dynamic passive walking robot with two legs and knees. The International Journal of Robotics Research, 2001, 20(7): 607-615
131 M. W. Spong. Underactuated Mechanical Systems. Control Problems in Robotics and Automation, 1998, 230: 135-150
132 M. W. Spong. The swing up control problem for the Acrobot. IEEE Control Systems, 1995, 15: 49-55
133 Vafa, Z., Dubowsky, S.. The kinematics and dynamics of space manipulators: The virtual manipulator approach. Int. J. of Robotics Research, 1990, 9(4): 3-21
134 K. Y. Pettersen, O. Egeland. Robust Control of an Underactuated Surface Vessel with Thruster Dynamics. Proceedings of the American Control Conference, 1997: 3411-3415
135 Frederic Mazenc, Kristin Pettersen, Henk Nijmeijer. Global Uniform Asymptotic Stabilization of an Underactuated Surface Vessel. IEEE Transactions on automatic control, 2002, 47(10): 1759-1762
136 K. D. Do, Z. P. Jiang, J. Pan. Robust adaptive path following of underactuated ships. Proceedings of the 41th IEEE Conference on Decision and Control Las Vegas, Nevada USA, 2002,12:3243-3248
137赵铁石,李娜.蛇形机器人动力学建模的虚设机构法.机械工程学报, 2007, 43: 66-71
2周玉林,高峰.仿人机器人构型.机械工程学报, 2006, 42(11): 66-74
3刘杰,张玉茹.机器人灵巧手抓持分类器的设计与实现.机器人, 2003, 25(3): 259-263
4彭光正,余麟,刘昊.气动人工肌肉驱动仿人灵巧手的结构设计.北京理工大学学报, 2006, 7: 593-597
5邹海荣,龚振邦,罗均.仿生眼的研究现状与发展趋势.机器人, 2005, 27(05): 470-474
6金振林,曹舜,高峰.新型机器人肩关节及其运动学分析.中国机械工程, 2009, 20(14): 1639-1642
7范顺成,韩书葵,谷慧茹.两足步行机器人并联腿机构的稳定性分析.河北工业大学学报, 2004, 33(1): 27-31
8潘智昊,谢少荣,罗均,等.仿生双目异向运动控制系统.制造业自动化, 2009, 31(1): 34-37
9刘伟,齐晓慧.基于视觉的机械手臂自主抓物的实现.自动测量与控制, 2008, 27(12): 79-80
10辛菁,刘丁,杨延西.基于图像的机器人视觉伺服免疫控制.仪器仪表学报, 2008, 29 (11): 2253-2259
11石玉秋,孙炜,孙洪淋.基于小波网络的机器人视觉伺服控制研究.微计算机信息, 2007, 23(7-2): 214-216
12陈辉,宋爱国,金世俊.带有力觉和触觉临场感的灵巧手主从系统的设计.机器人, 1998, 20(6): 438-448
13单保祥,王琪民,杨浩涌.微型触觉传感器敏感单元的分析和测试.中国科学技术大学学报, 1999, 29(4): 415-420
14胡军,李嘉,刘文江,等.基于CMAC的触觉传感信号自适应逆滤波器设计.微电子学与计算机, 2003, 8: 62-65
15黄英,明小慧,向蓓. A New Design of Flexible Three-Dimension Force Tactile Sensor of Robot.传感技术学报, 2008, 21(10): 1696-1699
16刘清君,许改霞,徐莹.仿生嗅觉神经芯片的研究进展.国外医学生物医学工程分册, 2005, 28(1): 56-61
17庄哲民,黄惟一.机器人人工嗅觉系统设计.东南大学学报, 2004, 34(1): 28-31
18李界家,吴成东,朱栋华.基于神经网络的人工嗅觉系统设计.自动化仪表, 2003, 24(4): 17-19
19窦振中.模糊逻辑控制技术及其应用(第1版).北京:北京航空航天大学出版社, 1995: 1-33
20赵林明,胡浩云,魏德华,等著.多层前向人工神经网络.郑州:黄河水利出版社, 1999: 1-7
21丁希仑,李海涛,解玉文.基于Internet的拟人双臂机器人遥操作系统的研究.高技术通讯, 2006, 16(8): 808-812
22吴伟国,李小宁,王瑜.类人机器人腰部关节平衡作用研究与仿真.机械设计与制造, 2006, 5: 112-114
23杨玉贵,彭光正,王毅枫.气动人工肌肉驱动的双臂机器人及其协调控制研究进展.机床与液压, 2008, 36(4): 181-184
24 Chang W. C., Lee S. A.. Autonomous vision-based pose control of mobile robots with tele-supervision. Proc of the IEEE International Conf on Control Applications. Piscataway, NJ, USA: IEEE, 2004: 1049-1054
25 Marchand E., Chaumette F.. Feature tracking for visual servoingpurposes. Robotics and Autonomous Systems, 2005, 52(1): 53-70
26 Edward G.Freedman. Interactions between eye and head control signals can account for movement kinematics. Biological Cybernetics, 2001, 84(6): 453-462.
27 http://tech.sina.com.cn/ology/2000-06-10/27785.shtml
28李贻斌.现代科技革命与机器人的发展.山东交通学院学报, 2002, 10(4): 53-74
29李艳杰,徐继宁,王侃.仿人机器人发展现状及其腰关节的作用.沈阳工业学院学报, 2004, 23(1): 18-23
30张炜,美浓地池一.从日本机器人技术的现状看机器人技术产业化发展.机器人技术与应用, 2006, 3: 1-5
31柯显信.仿人形机器人双足动态步行研究. [上海大学博士学位论文]. 2005: 1-10
32刘英卓.拟人形机器人建模、控制与协调研究. [中国科学院沈阳自动化研究所博士学位论文]. 2003: 1-21
33 J. Butterfab, M. Grebenstein, H. Liu, et al. DLR-Hand II: Next Generation of Adextrous Robot Hand. IEEE International Conference on Robotics and Automation, Seoul, Korea,2001:109-114
34冯金光,周华平,马宏绪.基于DSP的仿人机器人运动控制器设计.工业仪表与自动化装置, 2005, 2: 67-69
35杨庆,马宏绪. CMAC在仿人机器人逆运动学计算中的应用.机器人技术, 2006, 22(3-2): 187-208
36朱志斌,王岩,陈兴林.一种双足机器人实时步态规划方法及相关数值算法.机器人, 2008, 30(6): 521-527
37刘伊威,金明河. D LR/HIT仿人机器人灵巧手的设计.机械制造, 2006, 44(507): 32-35
38赵大威,姜力,金明河,等.仿人型机器人手的力矩保持功能及控制系统.电机与控制学报, 2007, 11(5): 497-501
39吴伟国,宋策,孟庆梅.仿人头像机器人“H&Frobot-Ш”语音及口形系统研制与实验.机械设计, 2008, 25(1): 15-19
40刘江华,程君实,弥佳品.基于视觉的动态手势识别及其在仿人机器人交互中的应用.机器人, 2002, 24(3): 197-216
41姜山,程君实,陈佳品,等.基于多目标遗传算法的仿人机器人中枢神经运动控制器的设计.机器人, 2001, 23(1): 58-67
42彭娟春,顾立忠,苏剑波.基于Camshift和Kalman滤波的仿人机器人手势跟踪.上海交通大学学报, 2006, 40(7): 1162-1165
43余蕾斌,曹其新,孙毅军.基于压应力中心的仿人机器人离散轨迹运动控制.上海交通大学学报. 2007, 41(8): 1263-1266
44陈健,雷旭升,苏剑波.基于智能体的仿人机器人分层控制系统.高技术通讯, 2007, 17(6): 586-590
45唐粲,贠超,刘达. CT导航微创外科混联机器人拓扑结构分析.机器人, 2008, 30(2):107-111
46 Elif Deryaübeyli. Implementing eigenvector methods/probabilistic neural networks for analysis of EEG signals. Neural Networks, 2008, 21(9): 1410-1417
47 Olivia Mendoza, Patricia Melin, Guillermo Licea. A hybrid approach for image recognition combining type-2 fuzzy logic, modular neural networks and the Sugeno integral. Information Sciences, 2009, 179(13): 2078-2101
48 Lisheng Xu, Max Q. H., Meng, Kuanquan Wang. Pulse images recognition using fuzzy neural network. Expert Systems with Applications, 2009, 36(2): 3805-3811
49 Monica Bianchini, Marco Maggini, Lorenzo Sarti. Recursive Neural Networks and Their Applications to Image Processing. Advances in Imaging and Electron Physics, 2006, 140: 1-60
50 Ren Shuyan Pu Zhaobang Zhuang Zhitao. Image filter arithmetic based on fuzzy neural network .Chinese Journal of Scientific Instrument, 2006, (S1): 4
51王秀英.基于BP神经网络的故障模式识别与应用.机电工程技术, 2008, 37(10): 103-118
52 Karayiannis N. B., Xiong Y. H.. Training reformulated radial basisfunction neural networks capable of identifying uncertainty in data clas-sification. Proc. of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. 2005: 1-8
53 R. Srinivasan, C. Wang, W. K. Ho, etc.. Context-based recognition of process states using neural networks .Chemical Engineering Science, 2005, 60(4): 935-949
54王丹凤,李书臣,翟春艳.基于神经网络参数优化的迭代学习控制算法.河南科技大学学报(自然科学版), 2008, 29(6): 42-44
55 Mehdi Ghatee, Ali Mohades. Motion planning in order to optimize the length and clearance applying a Hopfield neural network. Expert Systems with Applications, 2009, 36(3): 4688-4695
56 Erick CantúPaz, Chandrika Kamath. Evolving neural networks to identify bent-double galaxies in the FIRST survey. Neural Networks, 2003, 16(3-4): 507-517
57焦李成.神经网络的应用与实现.西安:西安电子科技大学出版社, 1991: 1-30
58 Y. P. Chu, C. M. Hsieh. An artificial neural network model with modified perceptron algorithm. Parallel Computing, 1992, 18(9): 983-996
59 Hopfield J J.. Neural Networks and Physical Systems with Emergent Collective Computational Abilities. Proc of the National Academy of Sciences of the United States of America, 1982, 79(8): 2554-2558
60胡守仁.神经网络导论.长沙:国防科技大学出版社, 1993: 1-55
61 J. J. Zhu, W. P. Xiao. Intelligent control of time-varying dynamical systems using CMAC artificial neural network. Mathematical and Computer Modelling, 1995, 21(1-2): 89-107
62 Juan Ignacio, Mulero-Martínez. Analysis of the errors in the modelling of manipulators with Gaussian RBF neural networks. Neurocomputing, 2009, 72(7-9): 1969-1978
63芮执元,孙雪莲,剡昌锋.基于模糊神经网络的蛇型机器人的智能控制.航空制造技术, 2005, 1: 71-74
64 T. Chatchanayuenyong, M. Parnichkun. Neural network based-time optimal sliding mode control for an autonomous underwater robot. Mechatronics, 2006, 16(8): 471-478
65高建树,邢志伟,张宏波.基于观测器的水下机器人神经网络自适应控制.机器人, 2004,26(6): 515-518
66昝鹏,颜国正,于莲芝.基于神经网络PID控制的柔性微机器人系统.机器人, 2007, 29(3): 219-229
67 Dai bing Zhang, De wen Hu, Lin-cheng Shen. A Bionic Neural Network for Fish-Robot Locomotion. Journal of Bionic Engineering, 2006, 3(4): 187-194
68王洪斌,李铁龙,郭继丽.机器人的神经网络鲁棒轨迹跟踪控制.电机与控制学报, 2005, 9(2): 145-150
69 Masanori Sato, Atushi Kanda, Kazuo Ishii. Adaptive control of nonlinear PID-based analog neural networks for a nonholonomic mobile robot. Neurocomputing, 2008, 71(7-9): 1561-1565
70 ?ahin Yildirim. Design of a proposed neural network control system for trajectory controlling of walking robots. Simulation Modelling Practice and Theory, 2008, 16(3): 368-378
71 Christophe Sabourin, Olivier Bruneau. Robustness of the dynamic walk of a biped robot subjected to disturbing external forces by using CMAC neural networks. Robotics and Autonomous Systems, 2005, 51(2-3): 81-99
72李霞,谢涛,陈维山.基于神经网络的双足机器人逆运动学求解.机械设计, 2003, 20(4): 36-39
73陈华志,谢存禧,曾德怀.基于神经网络的移动机器人路径规划算法的仿真.华南理工大学学报(自然科学版), 2003, 31(6): 56-59
74高峻峣,陆际联.轮式机器人遗传模糊神经网络转向控制.北京理工大学学报, 2003, 23(2): 176-180
75柳玉甜,蒋静坪.基于多模型和小脑模型关节控制器神经网络的移动机器人故障诊断.电工技术学报, 2007, 22(3): 153-158
76 L. A. Zadeh. Fuzzy sets. Information and Control, 1965, 8:338-353
77 K. Tanaka and M. Sugeno. Stability analysis and design of fuzzy control systems. Fuzzy Sets Syst., 1992, 45: 135-156
78 T. Takagi and M. Sugeno. Fuzzy identification of systems and its pplications to modeling and control. IEEE Trans. Syst. Man Cybern, 1985, 15: 116-132
79 L. X. Wang. Adaptive fuzzy systems and control: design and stability analysis. Englewood Cliffs, NJ: Prentice-Hall, 1994
80 E. H. Mamadani. Application of fuzzy alyorithms for simple dynamic plant. Proc. IEE., 1974,121: 1585-1588
81宋永端,高为炳.用于机器人轨迹跟踪的变结构控制.控制理论与应用, 1991,8(1):265-268
82 Y. D. Song. Path Tracking Control of Robot Using Variable Structure Model. Control Theory and Application. Control Theory and Control Application, 1991, 7(1): 201-204
83 C. M. Lin, T. Hiyama. Application of Fuzzy Logic Control to A Manipulator. Robot and Automation, 1991, 7(5): 688-691
84邓辉,孙富春,孙增圻.机械手的模糊逆模型鲁棒控制.自动化学报, 2001, 27(4): 521-530
85陈勇;吕霞付.基于模糊控制的放射性试剂分装机器人,仪器仪表学报, 2009, 30(2): 330-334
86洪昭斌,陈力.漂浮基双臂空间机器人系统的模糊神经网络自学习控制.机器人, 2008, 30(5): 435-439
87 Miller W. T. Real-time neural network control of a bipedwalking robot. IEEE Control Systems Magazine. 1994, 14: 14-48
88方道星,余跃庆,陈炜.基于模糊控制的2R欠驱动机器人位置控制.机械工程学报, 2008, 44(1): 144-154
89 Arimoto S., Kawamura S., M. iyazaki F.. Better operation of robots by learning. Journal of Robotic Systems, 1984, 1(2): 123-140
90 Hyo-Sung Ahn, Kevin L. Moore, YangQuan Chen. Stability analysis of discrete-time iterative learning control systems with interval uncertainty. Automatica, 2007, 43: 892-902
91孙明轩,黄宝健.迭代学习控制.北京:国防工业出版社, 1999: 4-9, 15-20, 73-75
92 Sun M. X., Wang D. W.. Iterative learning control with initial rectifying action. Automatica, 2002, 38(7): 1177-1182
93 Arif M., Ishihara T., Inooka H.. Iterative learning control using information data base. Journal of Intelligent and Robotic Systems, 1999, 25(1): 27-41
94 Tian S. P., Xie S. L., Fu X. L.. Fast algorithm of iterative learning control. Journal of South China University of Technology (Natural Science Edition), 2002, 30(5): 37-40
95张朝霞,王华奎.模糊神经网络及其在信道均衡中的应用.科技情报开发与经, 2005, 15(16): 151-158
96王耀南,孙炜.基于模糊神经网络的机器人自学习控制.电机与控制学报, 2001, 5 (2): 92-102
97白萍,方廷健,葛运健.基于神经网络补偿的机器人稳定自适应控制.模式识别与人工智能, 2001, 14(2): 162-165
98吴成东,武荣文,张俊杰.机器人神经网络控制研究进展.沈阳建筑工程学院学报, 1998, 14(1): 96-100
99金耀初,蒋静坪.一类非线性系统的模糊变结构控制及应用.控制与决策, 1992, 7(1): 36-40
100徐敏,林辉. ILC理论与应用新进展.控制理论与应用, 2003, 22(1): 4-7
101 Choi J., Park H. J.. Use of Networks in Iterative Learning Control Systems. Int. J. Systems Science, 2000, 31(10):1227-1239
102 Xu J., Vigwanathna B., Qu Z.. Robust iterative learning control for a class of nonlinear systems. Automatica, 1998, 34(8): 983-988
103 Xu J., Vigwanathna B.. Adaptive robust learning control with dead zone scheme. Automatica, 2000, 36(1): 91-99
104郭毓,申晓宁,陈庆伟,等.一类高阶线性时变系统自适应迭代学习辨识.兵工学报, 2008, 29(4): 454-458
105李研彪.新型6-DOF串并混联拟人机械臂的性能分析与设计. [燕山大学工学博士学位论文]. 2008: 40, 58-80
106郭祖华,陈五一,陈鼎昌. 6-UPS型并联机构的刚体动力学模型.机械工程学报, 2002, 38(11): 53-57
107 Gosselin C. M.. The optimum design of robotic manipulators using dexterity indices. Journal of Robotics and Autonomous systems, 1993, 9(4): 213-226
108黄田,曾宪菁,曾子平,等.等顶锥角3自由度球面并联机构的全参数解析尺度综合.机械工程学报, 2000, 36(8): 15-19
109 Xin-Jun Liu, Zhen-lin Jin, Feng Gao. Optimum design of 3-DOF spherical parallel manipulators with respect to the conditions and stiffness indices. Mechanism and Machine Theory, 2000, 35: 1257-1267
110高征,高峰.球面3自由度并联机构的正解分析新方法.机械设计与制造, 2006, 9: 122-124
111何开明.基于球面三角学的球面并联机构位姿正解.武汉理工大学学报, 2003, 25(6): 46-48
112张立杰,刘辛军.球面三自由度并联机器人可达工作空间的研究.中国机械工程, 2001, 12(10): 1122-1124
113孙立宁,刘宇,祝宇虹.一种用于腕关节的球面三自由度并联解耦机构位置分析.中国机械工程, 2003, 14(10): 831-833
114李研彪,金振林.球面三自由度机器人的力矩输入均衡性能分析与设计.光学精密工程, 2007, 15(5): 730-734
115赖一楠,张广玉,段志鸣,等.面向控制的3-RRR球面并联机构正运动学实时解法.中国机械工程, 2003, 14(2): 113-115
116许建新,侯忠生.学习控制的现状与展望.自动化学报, 2005, 31(6): 943-955
117代颖.不确定性机器人鲁棒自适应控制方法研究. [西安交通大学博士学位论文]. 1998: 11-32
118 Yiannis Karayiannidis, George Rovithakis, Zoe Dou- lgeri. Force/position tracking for a robotic manipulator in compliant contact with a surface using neuro- adaptive control. Automatica, 2007, 43(7): 1281-1288
119 Luis J. Ricalde, Edgar N. Sanchez. Output tracking with constrained inputs via inverse optimal adaptive recurrent neural control. Engineering Application of Artificial Intelligence, 2008, 21(4): 591-603
120 Fathi Fourati, Mohamed Chtourou, Mohamed Kamoun. Stabilization of unknown nonlinear systems using neural networks. Applied Soft Computing, 2008, 3, 8(2): 1121-1130
121 Montambault S., Gosselin C. M.. Analysis of underactuated mechanical grippers. ASME Journal Of Mechanical Design, 2001,123(3): 367-374
122何广平,陆震,王凤翔.欠驱动冗余度机器人运动优化控制.宇航学报, 2002, 23(5): 16-20
123 A. De Luca, G. Oriolo. Stabilization of the Acrobot via iterative state steering. 1998 IEEE Int. Conf. on Robotics and Automation, 1998: 3581-3587
124 A. De Luca, R. Mattone, G. Oriolo. Stabilization of underactuated robots: Theory and experiments for a planar 2R manipulator. 1997 IEEE Int. Conf. On Robotics and Automation, 1997: 3274-3280
125 Alessandro De Luca, Giuseppe Oriolo. Trajectory Planning and Control for Planar Robots with Passive Last Joint. The International Journal Of Robotics Research, 2002: 575-590
126 Mahmut Reyhanoglu, Arjan vander schaft, N. Harris McClamroch, etc.. Dynamics and Control of a class of underactuateed Mechnical Systems. IEEE Transactions on Automatic Control, 1999, 44(9): 1663-1671
127 M. Bergerman, C. Lee, Y. Xu. A dynamic coupling index for underactuated manipul ators. J. of Robotic Systems, 1995, 12(10): 693-707
128 Y. Liu, Y. Xu, M. Bergerman. Cooperation control of multiple manipulators with passive joints. IEEE Transactions on Robotics and Automation, 1999, 15(2): 258-267
129 Xuzhi LAI, Jin-Hua SHE, Yasuhiro OHYAMA, etc.. A Fuzzy Control Strategy for Acrobots Combining Model-Free and Model-Based Control. IEE Proceedings Control Theory and Applications, 1999, 146(6): 1-17
130 S. H. Collins, M. Wisse, A. Ruina. A three-dimensional dynamic passive walking robot with two legs and knees. The International Journal of Robotics Research, 2001, 20(7): 607-615
131 M. W. Spong. Underactuated Mechanical Systems. Control Problems in Robotics and Automation, 1998, 230: 135-150
132 M. W. Spong. The swing up control problem for the Acrobot. IEEE Control Systems, 1995, 15: 49-55
133 Vafa, Z., Dubowsky, S.. The kinematics and dynamics of space manipulators: The virtual manipulator approach. Int. J. of Robotics Research, 1990, 9(4): 3-21
134 K. Y. Pettersen, O. Egeland. Robust Control of an Underactuated Surface Vessel with Thruster Dynamics. Proceedings of the American Control Conference, 1997: 3411-3415
135 Frederic Mazenc, Kristin Pettersen, Henk Nijmeijer. Global Uniform Asymptotic Stabilization of an Underactuated Surface Vessel. IEEE Transactions on automatic control, 2002, 47(10): 1759-1762
136 K. D. Do, Z. P. Jiang, J. Pan. Robust adaptive path following of underactuated ships. Proceedings of the 41th IEEE Conference on Decision and Control Las Vegas, Nevada USA, 2002,12:3243-3248
137赵铁石,李娜.蛇形机器人动力学建模的虚设机构法.机械工程学报, 2007, 43: 66-71
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