基于视觉伺服的吊车防摆控制研究
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摘要
视觉伺服技术是利用计算机视觉原理,对采集到的图像信息进行快速处理和特征提取,进而提供反馈信息实现系统的闭环控制。视觉伺服系统是以视觉作为获取外界信息的途径,具有信息量大和智能化水平高等特点,目前在工业机器人、微操作机器人和空间飞行器对接系统等领域得到了广泛应用。吊车作为一种搬运工具,在工业生产中发挥着重要作用,如何消除货物在吊运过程中的摆动,进而提高吊车的工作效率一直是控制领域研究的经典问题。抑制摆动的基础是实现重物摆角的有效测量,传统的摆角测量装置安装于吊车系统内部,是一种接触式的测量方法,具有机械结构复杂、独立性差等缺点。本文将视觉伺服技术引入到吊车防摆控制中来,利用计算机视觉的方法实现重物摆角的无接触式测量,并采用逆系统非线性控制策略实现吊车系统的定位防摆控制。
本文首先介绍了摆角视觉测量系统的硬件组成,针对摆角的计算机视觉测量需求,本文提出了一套快速有效的图像处理和特征提取方法,并对这种测量方法的可行性进行了分析与实验。结果表明这种计算机视觉测量方法具有较高的分辨率和较宽的测量范围,能准确地测量出钢丝绳的摆角,并满足控制的实时性要求,可以用于吊车系统的定位防摆控制中。
根据吊车系统的物理模型,本文应用分析力学的拉格朗日方程建立了吊车系统的数学模型。从本质上看,吊车是一个多变量、非线性、强耦合的欠驱动机械系统,它的控制输入个数少于系统自由度个数,存在着模型复杂、难于控制等特点。为此本文应用逆系统非线性控制方法对吊车系统进行了解耦,进而分别设计位置、绳长伺服控制器和摆动抑制器,提出了变绳长情况下吊车定位防摆控制策略。仿真实验结果表明,该控制方案能够有效地实现吊车系统的准确定位和防摆。
最后在吊车实物实验系统平台上,采用摆角计算机视觉测量方法,应用逆系统非线性控制策略,进行了实物实验,实现了基于视觉伺服的吊车定位防摆控制,同时所设计的控制器对于重物质量的变化具有很强的鲁棒性。
Vision servo technique utilizes the computer vision theory for high-speed image information processing and feature extraction to realize closed-loop control of the system based on the feedback information. Using vision as its main approach to obtain outside information, vision servo system features extensive information and high intelligence and therefore is presently widely used in the field of industrial robot, micro-operation robot and spacecraft docking system. At the same time, crane, as a kind of transfer tools, plays a significant role in industrial manufacturing. Consequently, how the swaying during goods lifting can be eliminated to achieve high working efficiency of the crane has always been a classical concern for control study. The key point to damping out swaying is the accurate measurement of the angle. Using contact measuring method, traditional angle measuring devices, however, are installed inside the crane system and characterize complicated mechanical structure and poor ability of independence accordingly. The thesis introduces vision servo technique into the anti-swaying control over the crane. Moreover, non-contact measurement is achieved based on computer vision method and inverse system nonlinear control strategy is employed to realize the positioning and anti-swaying control of the crane system.
This paper initially focuses on hardware components of angle vision measuring system. In the light of computer vision measurement requirement of the angle, a set of rapid and effective image processing and feature extraction methods is proposed and the feasibility of these methods is analyzed and tested as well in this paper. The experimental results show that the computer vision measuring method, which has a big distinguishable rate, a wide range of measurement, can guarantee the measuring accuracy of the angle and satisfy the need of real-time control; therefore can be used in the positioning and anti-swaying control of the crane system.
Based on the physical model of the crane system, this paper builds up a mathematical model in terms of Langrange equation of analytical mechanics. In essence, as a multi-variable, nonlinear, strong-coupled underactuated mechanical system, the crane is complex in model and difficult to control because its number of control input is less than that of system’s degree of freedom. To cope with this problem, the inverse system nonlinear control method is applied firstly for the decoupling of the crane system, then a position and cord length servo controller and swaying controller are designed to put forward the positioning and anti-swaying control strategy of the crane in case of changeable cord lengths. The simulation results demonstrate that the proposed control strategy can realize the accurate positioning and anti-swaying of the crane system.
Finally, computer vision measuring method of the angle and inverse system nonlinear control strategy are employed to conduct object experiments on the crane experimental system platform, and positioning and anti-swaying control over the crane is realized based on vision servo thereby. Moreover, the designed controller has good robustness for variable mass of the payload.
本文首先介绍了摆角视觉测量系统的硬件组成,针对摆角的计算机视觉测量需求,本文提出了一套快速有效的图像处理和特征提取方法,并对这种测量方法的可行性进行了分析与实验。结果表明这种计算机视觉测量方法具有较高的分辨率和较宽的测量范围,能准确地测量出钢丝绳的摆角,并满足控制的实时性要求,可以用于吊车系统的定位防摆控制中。
根据吊车系统的物理模型,本文应用分析力学的拉格朗日方程建立了吊车系统的数学模型。从本质上看,吊车是一个多变量、非线性、强耦合的欠驱动机械系统,它的控制输入个数少于系统自由度个数,存在着模型复杂、难于控制等特点。为此本文应用逆系统非线性控制方法对吊车系统进行了解耦,进而分别设计位置、绳长伺服控制器和摆动抑制器,提出了变绳长情况下吊车定位防摆控制策略。仿真实验结果表明,该控制方案能够有效地实现吊车系统的准确定位和防摆。
最后在吊车实物实验系统平台上,采用摆角计算机视觉测量方法,应用逆系统非线性控制策略,进行了实物实验,实现了基于视觉伺服的吊车定位防摆控制,同时所设计的控制器对于重物质量的变化具有很强的鲁棒性。
Vision servo technique utilizes the computer vision theory for high-speed image information processing and feature extraction to realize closed-loop control of the system based on the feedback information. Using vision as its main approach to obtain outside information, vision servo system features extensive information and high intelligence and therefore is presently widely used in the field of industrial robot, micro-operation robot and spacecraft docking system. At the same time, crane, as a kind of transfer tools, plays a significant role in industrial manufacturing. Consequently, how the swaying during goods lifting can be eliminated to achieve high working efficiency of the crane has always been a classical concern for control study. The key point to damping out swaying is the accurate measurement of the angle. Using contact measuring method, traditional angle measuring devices, however, are installed inside the crane system and characterize complicated mechanical structure and poor ability of independence accordingly. The thesis introduces vision servo technique into the anti-swaying control over the crane. Moreover, non-contact measurement is achieved based on computer vision method and inverse system nonlinear control strategy is employed to realize the positioning and anti-swaying control of the crane system.
This paper initially focuses on hardware components of angle vision measuring system. In the light of computer vision measurement requirement of the angle, a set of rapid and effective image processing and feature extraction methods is proposed and the feasibility of these methods is analyzed and tested as well in this paper. The experimental results show that the computer vision measuring method, which has a big distinguishable rate, a wide range of measurement, can guarantee the measuring accuracy of the angle and satisfy the need of real-time control; therefore can be used in the positioning and anti-swaying control of the crane system.
Based on the physical model of the crane system, this paper builds up a mathematical model in terms of Langrange equation of analytical mechanics. In essence, as a multi-variable, nonlinear, strong-coupled underactuated mechanical system, the crane is complex in model and difficult to control because its number of control input is less than that of system’s degree of freedom. To cope with this problem, the inverse system nonlinear control method is applied firstly for the decoupling of the crane system, then a position and cord length servo controller and swaying controller are designed to put forward the positioning and anti-swaying control strategy of the crane in case of changeable cord lengths. The simulation results demonstrate that the proposed control strategy can realize the accurate positioning and anti-swaying of the crane system.
Finally, computer vision measuring method of the angle and inverse system nonlinear control strategy are employed to conduct object experiments on the crane experimental system platform, and positioning and anti-swaying control over the crane is realized based on vision servo thereby. Moreover, the designed controller has good robustness for variable mass of the payload.
引文
1张晓华.控制系统数字仿真与CAD.机械工业出版社. 2005
2刘曙光,刘明远,何钺.机器视觉及其应用.河北科技大学学报. 2000,21(4):11-15
3高淑玲.桥式吊车防摆控制.自动化技术与应用. 1988,(7):1-4
4华克强,高淑玲,朱齐丹.吊车防摆技术的研究.控制理论和应用. 1992,9(6): 631-637
5邹军,陈志坚.桥式起重机水平运行及抓斗防摆规律研究.山东大学学报. 1998,33(4):393-397
6李伟.基于时间最优的起重机消摆控制策略.山东工业大学学报. 1998,28(2):107-111
7齐伯文,张广春.塔式起重机智能控制系统的最优反馈控制.哈尔滨建筑工程学院学报. 1995,28(1):90-95
8梁春燕,贾青.提升起重机的时滞滤波消摆控制.应用科学学报. 2001,19(2):157-160
9刘殿通,易建强,谭民.一类非线性系统的自适应滑模模糊控制.自动化学报. 2004,30(1):143-150
10 H. H. Lee. Modeling and Control of a Three-Dimensional Overhead Crane. Journal of Dynamic Systems, Measurement and Control. 1998,120(4):471-476
11 D. C. D. Oguamanam, J. S. Hansen. Dynamics of a Three-Dimensional Overhead Crane System. Journal of Sound and Vibration. 2001,242(3):411-426
12 S. K. Cho, H. H. Lee. An Anti-Swing Control of a 3-Dimensional Overhead Crane. Proceedings of the American Control Conference, Chicago, Illinois, the USA, 2000,2:1037-1041
13 Y. S. Kim, H. S. Seo, S. K. Sul. A New Anti-Sway Control Scheme for Trolley Crane System. IEEE Industry Applications Society Annual Meeting, Chicago, Illinois, the USA, 2001,1:548-552
14 A. Ciua, C. Sentzu, G. Usai. Observer-Controller Design for Cranes Via Lyapunov Equivalence. Automatica. 1999,35(4):669-678
15 A. Piazzi, A. Visioli. Optimal Dynamic-Inversion-Based Control of an Overhead Crane. Control Theory and Applications. 2002,149(5):405-411
16 Z. H. Wang, B. W. Surgenor. A Problem with the LQ Control of Overhead Cranes. Journal of Dynamic Systems, Measurement and Control. 2006,128(2):436-440
17 S. Yamada, H. Fujikawa, O. Takeuchi, Y. Wakasugi. Fuzzy Control of the Roof Crane. The 15th Annual Conference of IEEE, Philadelphia, Pennsylvania, the USA, 1989,4:709-714
18 A. Benhidjeb, G. L. Gissinger. Fuzzy Control of an Overhead Crane Performance Comparison with Classic Control. Control Engineering Practice. 1995,3(12):1687-1696
19 J. A. Mendez, L. Acosta, L. Moreno, A. Hamilton, G. N. Marichal. Design of a Neural Network Based Self-Tuning Controller for an Overhead Crane. IEEE Conference on Control Applications, 1998,1:168-171
20 T. Burg, D. Dawson, C. Rahn, W. Rhodes. Nonlinear Control of an Overhead Crane via the Saturating Control Approach of Teel. Proceedings of 1996 IEEE International Conference on Robotics and Automation, Minneapolis, Minnesota, the USA, 1996,4:3155-3160
21 K. Yoshida, H. Kawabe. A Design of Saturating Control with a Guaranteed Cost and Its Application to the Crane Control. IEEE Transactions on Automation Control. 1992,37(1):121-127
22 J. Collado, R. Lozano, I. Fantoni. Control of Convey-Crane Based on Passivity. Proceedings of the American Control Conference, Chicago, Illinois, the USA, 2000,2:1260-1264
23 Y. Fang, W. E. Dixon, D. M. Dawson. Nonlinear Coupling Control Laws for an Underactuated Overhead Crane System. IEEE/ASME Transactions on Mechatronics. 2003,8(3):418-423
24 H. M. Omar, A. H. Nayfeh. Gantry Cranes Gain Scheduling Feedback Control with Friction Compensation. Journal of Sound and Vibration. 2004,10(2):269-289
25 L. Moreno, L. Acosta, J. A.Mendez. A Self-Tuning Neuromorphic Controller: Application to the Crane Problem. Control Engineering Practice. 1998,6(12):1475-1483
26 L. F. Mendonca, J. M. Sousa, J. S. Costa. Optimization Problems in Multivariable Fuzzy Predictive Control. International Journal of ApproximateReasoning. 2004,36:199-221
27 S. Hutchinson, G. D. Hager, P. I. Corke. A Tutorial on Visual Servo Control. IEEE Transactions on Robotics and Automation. 1996,12(5):651-670
28郭峰,曹其新,赵言正,朱伟华.基于视觉伺服的倒立摆实验平台的研究.机械设计与研究. 2003,19(4):62-64
29但堂咏.岸边桥式起重机智能防摇控制机理研究.武汉理工大学硕士学位论文. 2005
30 T. Matsuo, R. Yoshino, H. Suemitsu, K. Nakano. Nominal Performance Recovery by PID+Q Controller and Its Application to Antisway Control of Crane Lifter with Visual Feedback. IEEE Transactions on Control Systems Technology. 2004,12(1):156-166
31 H. Osumi, A. Miura, S. Eiraku. Positioning of Wire Suspension System Using CCD Cameras. IEEE International Conference on Intelligent Robots and Systems, 2005,8:1665-1670
32 M. E. Magana, F. Holzapfel. Fuzzy-Logic Control of an Inverted Pendulum with Vision Feedback. IEEE Transactions on Education. 1998,42(2):165-170
33 L. Wenzel, N. Vazquez, D. Nair, R. Jamal. Computer Vision Based Inverted Pendulum. IEEE Instrumentation and Measurement Technology Conference, Baltimore, Maryland, the USA, 2000,3:1319-1323
34 E. P. Dadios, R. Baylon, R. D. Guzman, A. Florentino, R. M. Lee , Z. Zulueta. Vision Guided Ball-Beam Balancing System Using Fuzzy Logic. Industrial Electronics Conference, Nagoya, Japan, 2000,3:1973-1978
35 I. Petrovic, M. Brezak, R. Cupec. Machine Vision Based Control of the Ball and Beam. Proceedings of the 7th International Workshop on Advanced Motion Control, 2002:573-577
36陈书海,傅录祥.实用数字图像处理.科学出版社. 2005
37刘焕军,王耀南,段峰.机器视觉中的图像采集技术.电脑与信息技术. 2003,(1):18-21
38吴勃英.数值分析原理.科学出版社. 2003
39邱秉权.分析力学.中国铁道出版社. 1998
40哈尔滨工业大学理论力学教研室.理论力学.高等教育出版社. 1997
41张晓华.系统建模与仿真.清华大学出版社. 2006
42李春文,冯元琨.多变量非线性控制的逆系统方法.清华大学出版社. 1991
43陈庆伟,吕朝霞,胡维礼.基于逆系统方法的非线性内模控制.自动化学报. 2002,28(5):715-721
44李春文,苗原,冯元琨.非线性系统的逆系统方法(I).控制与决策. 1997,12(5):530-535
45李春文,苗原,冯元琨.非线性系统的逆系统方法(II).控制与决策. 1997,12(6):625-630
46高丙团.非线性控制及其在吊车防摆控制中的应用.哈尔滨工业大学硕士学位论文. 2004
47胡邵华.桥式吊车防摆控制技术研究.沈阳工业大学硕士学位论文. 2006
48夏德钤,翁贻方.自动控制理论.机械工业出版社. 2004
49薛定宇.控制系统计算机辅助设计—MATLAB语言及应用.清华大学出版社. 1996
50熊永波.吊车防摆实物仿真技术研究.哈尔滨工业大学硕士学位论文. 2003
51余明兴,吴明哲. Borland C++ Builder实例精解.清华大学出版社.2001
2刘曙光,刘明远,何钺.机器视觉及其应用.河北科技大学学报. 2000,21(4):11-15
3高淑玲.桥式吊车防摆控制.自动化技术与应用. 1988,(7):1-4
4华克强,高淑玲,朱齐丹.吊车防摆技术的研究.控制理论和应用. 1992,9(6): 631-637
5邹军,陈志坚.桥式起重机水平运行及抓斗防摆规律研究.山东大学学报. 1998,33(4):393-397
6李伟.基于时间最优的起重机消摆控制策略.山东工业大学学报. 1998,28(2):107-111
7齐伯文,张广春.塔式起重机智能控制系统的最优反馈控制.哈尔滨建筑工程学院学报. 1995,28(1):90-95
8梁春燕,贾青.提升起重机的时滞滤波消摆控制.应用科学学报. 2001,19(2):157-160
9刘殿通,易建强,谭民.一类非线性系统的自适应滑模模糊控制.自动化学报. 2004,30(1):143-150
10 H. H. Lee. Modeling and Control of a Three-Dimensional Overhead Crane. Journal of Dynamic Systems, Measurement and Control. 1998,120(4):471-476
11 D. C. D. Oguamanam, J. S. Hansen. Dynamics of a Three-Dimensional Overhead Crane System. Journal of Sound and Vibration. 2001,242(3):411-426
12 S. K. Cho, H. H. Lee. An Anti-Swing Control of a 3-Dimensional Overhead Crane. Proceedings of the American Control Conference, Chicago, Illinois, the USA, 2000,2:1037-1041
13 Y. S. Kim, H. S. Seo, S. K. Sul. A New Anti-Sway Control Scheme for Trolley Crane System. IEEE Industry Applications Society Annual Meeting, Chicago, Illinois, the USA, 2001,1:548-552
14 A. Ciua, C. Sentzu, G. Usai. Observer-Controller Design for Cranes Via Lyapunov Equivalence. Automatica. 1999,35(4):669-678
15 A. Piazzi, A. Visioli. Optimal Dynamic-Inversion-Based Control of an Overhead Crane. Control Theory and Applications. 2002,149(5):405-411
16 Z. H. Wang, B. W. Surgenor. A Problem with the LQ Control of Overhead Cranes. Journal of Dynamic Systems, Measurement and Control. 2006,128(2):436-440
17 S. Yamada, H. Fujikawa, O. Takeuchi, Y. Wakasugi. Fuzzy Control of the Roof Crane. The 15th Annual Conference of IEEE, Philadelphia, Pennsylvania, the USA, 1989,4:709-714
18 A. Benhidjeb, G. L. Gissinger. Fuzzy Control of an Overhead Crane Performance Comparison with Classic Control. Control Engineering Practice. 1995,3(12):1687-1696
19 J. A. Mendez, L. Acosta, L. Moreno, A. Hamilton, G. N. Marichal. Design of a Neural Network Based Self-Tuning Controller for an Overhead Crane. IEEE Conference on Control Applications, 1998,1:168-171
20 T. Burg, D. Dawson, C. Rahn, W. Rhodes. Nonlinear Control of an Overhead Crane via the Saturating Control Approach of Teel. Proceedings of 1996 IEEE International Conference on Robotics and Automation, Minneapolis, Minnesota, the USA, 1996,4:3155-3160
21 K. Yoshida, H. Kawabe. A Design of Saturating Control with a Guaranteed Cost and Its Application to the Crane Control. IEEE Transactions on Automation Control. 1992,37(1):121-127
22 J. Collado, R. Lozano, I. Fantoni. Control of Convey-Crane Based on Passivity. Proceedings of the American Control Conference, Chicago, Illinois, the USA, 2000,2:1260-1264
23 Y. Fang, W. E. Dixon, D. M. Dawson. Nonlinear Coupling Control Laws for an Underactuated Overhead Crane System. IEEE/ASME Transactions on Mechatronics. 2003,8(3):418-423
24 H. M. Omar, A. H. Nayfeh. Gantry Cranes Gain Scheduling Feedback Control with Friction Compensation. Journal of Sound and Vibration. 2004,10(2):269-289
25 L. Moreno, L. Acosta, J. A.Mendez. A Self-Tuning Neuromorphic Controller: Application to the Crane Problem. Control Engineering Practice. 1998,6(12):1475-1483
26 L. F. Mendonca, J. M. Sousa, J. S. Costa. Optimization Problems in Multivariable Fuzzy Predictive Control. International Journal of ApproximateReasoning. 2004,36:199-221
27 S. Hutchinson, G. D. Hager, P. I. Corke. A Tutorial on Visual Servo Control. IEEE Transactions on Robotics and Automation. 1996,12(5):651-670
28郭峰,曹其新,赵言正,朱伟华.基于视觉伺服的倒立摆实验平台的研究.机械设计与研究. 2003,19(4):62-64
29但堂咏.岸边桥式起重机智能防摇控制机理研究.武汉理工大学硕士学位论文. 2005
30 T. Matsuo, R. Yoshino, H. Suemitsu, K. Nakano. Nominal Performance Recovery by PID+Q Controller and Its Application to Antisway Control of Crane Lifter with Visual Feedback. IEEE Transactions on Control Systems Technology. 2004,12(1):156-166
31 H. Osumi, A. Miura, S. Eiraku. Positioning of Wire Suspension System Using CCD Cameras. IEEE International Conference on Intelligent Robots and Systems, 2005,8:1665-1670
32 M. E. Magana, F. Holzapfel. Fuzzy-Logic Control of an Inverted Pendulum with Vision Feedback. IEEE Transactions on Education. 1998,42(2):165-170
33 L. Wenzel, N. Vazquez, D. Nair, R. Jamal. Computer Vision Based Inverted Pendulum. IEEE Instrumentation and Measurement Technology Conference, Baltimore, Maryland, the USA, 2000,3:1319-1323
34 E. P. Dadios, R. Baylon, R. D. Guzman, A. Florentino, R. M. Lee , Z. Zulueta. Vision Guided Ball-Beam Balancing System Using Fuzzy Logic. Industrial Electronics Conference, Nagoya, Japan, 2000,3:1973-1978
35 I. Petrovic, M. Brezak, R. Cupec. Machine Vision Based Control of the Ball and Beam. Proceedings of the 7th International Workshop on Advanced Motion Control, 2002:573-577
36陈书海,傅录祥.实用数字图像处理.科学出版社. 2005
37刘焕军,王耀南,段峰.机器视觉中的图像采集技术.电脑与信息技术. 2003,(1):18-21
38吴勃英.数值分析原理.科学出版社. 2003
39邱秉权.分析力学.中国铁道出版社. 1998
40哈尔滨工业大学理论力学教研室.理论力学.高等教育出版社. 1997
41张晓华.系统建模与仿真.清华大学出版社. 2006
42李春文,冯元琨.多变量非线性控制的逆系统方法.清华大学出版社. 1991
43陈庆伟,吕朝霞,胡维礼.基于逆系统方法的非线性内模控制.自动化学报. 2002,28(5):715-721
44李春文,苗原,冯元琨.非线性系统的逆系统方法(I).控制与决策. 1997,12(5):530-535
45李春文,苗原,冯元琨.非线性系统的逆系统方法(II).控制与决策. 1997,12(6):625-630
46高丙团.非线性控制及其在吊车防摆控制中的应用.哈尔滨工业大学硕士学位论文. 2004
47胡邵华.桥式吊车防摆控制技术研究.沈阳工业大学硕士学位论文. 2006
48夏德钤,翁贻方.自动控制理论.机械工业出版社. 2004
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