滑块式虚拟轴机床高精度控制的研究
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摘要
虚拟轴机床虽然结构简单，却能够加工一般数控机床无法加工的复杂曲面，这是它最主要的优点。但是由于虚拟轴机床结构上的特点，各轴之间存在机械强耦合，所以每一轴的运动对其它轴都有很大的影响，则其控制方法与串联轴机床比相对复杂。如何实现虚拟轴机床的高精度控制，是一个必须解决的重要问题。本课题研究滑块式虚拟轴机床的高精度控制问题。
滑块式虚拟轴机床采用直线电动机作为驱动机构，因此伺服系统的控制对象就是直线电机。在本文中研究的滑块式虚拟轴机床驱动装置采用直线永磁交流电动机。
在以直线永磁同步伺服电动机为被控对象的伺服系统中，为满足高性能的要求，仔细考虑了能使伺服系统性能变坏的各种因素，包括：各轴之间的机械耦合扰动，永磁同步直线电机动子质量变化、摩擦系数变化等造成的模型参数不确定性，忽略电磁时间常数等因素造成的模型非结构化不确定性，以及电机运行期间存在磁密分布变化、时间谐波等产生的推力扰动等。为克服外界扰动及模型误差等不确定因素对系统造成的影响，提高伺服系统性能，并自动保证系统鲁棒稳定性，本文将H_∞控制律与负载扰动观测器相结合，应用于对位置伺服系统的IP控制当中，于是可以通过H_∞负载扰动观测器随时观测外界扰动并针对扰动给系统以实时的补偿以保证控制精度的要求。
同时本文又提出了一种用于补偿扰动的新型神经网络推力补偿器。由于它的权值具有明确的物理意义，并且在线调整的权值数量很少，所以它具备一般神经网络所没有的快速响应的性能。这种神经网络能够针对外界扰动给予系统实时的补偿，提高伺服系统的控制精度。
本文所提出的控制方案有严格的理论基础，经过了理论与实验的验证。在同时存在参数不确定性、未建模动态和有界扰动时，应用H_∞理论的分析、IP位置控制设计和神经网络使伺服系统可实现对其有多种不确定性的被控对象的精密控制。仿真结果表明所提出的方案具有强鲁棒性，其控制效果很好。
Although the structure of virtual axis machine tool is very simple, it can process the complex curved surface which can not be processed by general data control machine tool. But for the characteristics of the structure of virtual axis machine tool, there are strong mechanic coupling among every axis. Therefore, the motion of every axis will effect other axises. and the control method become relatively more complex than normal machine tools. How to realize the high precision control is an important problem must be solved. Our task is to study the high precision control of hexaglide virtual axis machine tool.
Line motor is adopted as driving machine in hexaglide virtual axis machine tool, so the control object of the servo system in the machine tool is line motor. Here line permanent magnetic AC motor is used as the driven equipment of the hexaglide virtual axis machine tools.
To satisfy high performance, many causes which will destroy the performance of the servo system are considered carefully in the system where line permanent magnetic servo motor is control object: the mechanic coupling disturbance among every axis, the mass change of the mover of line permanent magnetic motor, the uncertainties of the model parameters made by the change of the friction coefficient, the unstructured uncertainties caused by ignoring the electromagnetic time constant and the thrust fluctuations aroused by the varieties of the magnetic density distributions and the time harmonic. In order to reduce the effects on system brought by the outside disturbances and model errors, to improve the servo performances and to guarantee automatically the robust stability , the H_∞ robust control law is app led to the servo system in this paper and combined with the disturbance observer, therefore the control precision can be assured by using the data which is observed by the observer-to complement the disturba
nce of the environment at any moment.
At the same time a new type of neural network thrust compensator is proposed here. For
the clear physical meaning of its weight, and the little number of the en-line adjusted weight
this kind of neural network have the fast response performance which other neural networks
don't have. Therefore this neural network can give the system real-time compensation, and the proposed control scheme has a rigorous theoretic base and has been validated by the theory and experiment.
When uncertainties of the parameter, unmodeled dynamics and bounded perturbation '
exists simultaneously, the precision control of the control object which have many uncertainties can be realized in the servo system by using H∞ law analysis, IP position control design, and neural network.. The result of simulation indicates that this control scheme have strong robust and good control effect.
滑块式虚拟轴机床采用直线电动机作为驱动机构，因此伺服系统的控制对象就是直线电机。在本文中研究的滑块式虚拟轴机床驱动装置采用直线永磁交流电动机。
在以直线永磁同步伺服电动机为被控对象的伺服系统中，为满足高性能的要求，仔细考虑了能使伺服系统性能变坏的各种因素，包括：各轴之间的机械耦合扰动，永磁同步直线电机动子质量变化、摩擦系数变化等造成的模型参数不确定性，忽略电磁时间常数等因素造成的模型非结构化不确定性，以及电机运行期间存在磁密分布变化、时间谐波等产生的推力扰动等。为克服外界扰动及模型误差等不确定因素对系统造成的影响，提高伺服系统性能，并自动保证系统鲁棒稳定性，本文将H_∞控制律与负载扰动观测器相结合，应用于对位置伺服系统的IP控制当中，于是可以通过H_∞负载扰动观测器随时观测外界扰动并针对扰动给系统以实时的补偿以保证控制精度的要求。
同时本文又提出了一种用于补偿扰动的新型神经网络推力补偿器。由于它的权值具有明确的物理意义，并且在线调整的权值数量很少，所以它具备一般神经网络所没有的快速响应的性能。这种神经网络能够针对外界扰动给予系统实时的补偿，提高伺服系统的控制精度。
本文所提出的控制方案有严格的理论基础，经过了理论与实验的验证。在同时存在参数不确定性、未建模动态和有界扰动时，应用H_∞理论的分析、IP位置控制设计和神经网络使伺服系统可实现对其有多种不确定性的被控对象的精密控制。仿真结果表明所提出的方案具有强鲁棒性，其控制效果很好。
Although the structure of virtual axis machine tool is very simple, it can process the complex curved surface which can not be processed by general data control machine tool. But for the characteristics of the structure of virtual axis machine tool, there are strong mechanic coupling among every axis. Therefore, the motion of every axis will effect other axises. and the control method become relatively more complex than normal machine tools. How to realize the high precision control is an important problem must be solved. Our task is to study the high precision control of hexaglide virtual axis machine tool.
Line motor is adopted as driving machine in hexaglide virtual axis machine tool, so the control object of the servo system in the machine tool is line motor. Here line permanent magnetic AC motor is used as the driven equipment of the hexaglide virtual axis machine tools.
To satisfy high performance, many causes which will destroy the performance of the servo system are considered carefully in the system where line permanent magnetic servo motor is control object: the mechanic coupling disturbance among every axis, the mass change of the mover of line permanent magnetic motor, the uncertainties of the model parameters made by the change of the friction coefficient, the unstructured uncertainties caused by ignoring the electromagnetic time constant and the thrust fluctuations aroused by the varieties of the magnetic density distributions and the time harmonic. In order to reduce the effects on system brought by the outside disturbances and model errors, to improve the servo performances and to guarantee automatically the robust stability , the H_∞ robust control law is app led to the servo system in this paper and combined with the disturbance observer, therefore the control precision can be assured by using the data which is observed by the observer-to complement the disturba
nce of the environment at any moment.
At the same time a new type of neural network thrust compensator is proposed here. For
the clear physical meaning of its weight, and the little number of the en-line adjusted weight
this kind of neural network have the fast response performance which other neural networks
don't have. Therefore this neural network can give the system real-time compensation, and the proposed control scheme has a rigorous theoretic base and has been validated by the theory and experiment.
When uncertainties of the parameter, unmodeled dynamics and bounded perturbation '
exists simultaneously, the precision control of the control object which have many uncertainties can be realized in the servo system by using H∞ law analysis, IP position control design, and neural network.. The result of simulation indicates that this control scheme have strong robust and good control effect.
引文
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[2] D.Stewart. A Platform with 6 Degree of Freedom. Proc. Inst. Mech. Eng. 1965, 180:371-386.
[3] K. H. Hunt, "Structural Kinematics of In-Parallel-Actuated Robot-Arms," in ASME Journal of Mechanisms, Transmission, and Automation in Design, 1983, 105(5):705-712.
[4] H. M. Callion, D. T. Pham The Analysis of a Six Degrees of Freedom Work Station for Mechanized Assembly. In Proc. 5th World Congress on Theory of Machines and Mechanisms, 1979, 611-616.
[5] Ficher E.F.,"A Stewart Platform-Based Manipulator :General Theory and Practical Construction, "in the International Robotics Research, 1986, 5(2): 157-182.
[6] Sugimoto K., Kinematics and Dynamic Analysis of Parallel Manipulators by Means of Motor Algebra. Trans. ASME J, of Mechanics, Transmissions, and Automation in Design, 1987, 1109(3):139-143.
[7] 黄真．空间机构学．北京：机械工业出版社，1991．
[8] Client M. Gosselin and Wang Jiegao, "Singularity loci of Planar parallel manipulators with revolute actuators," in Robotics and Autonomous Systems, 1997, 21 (4): 377-398.
[9] Ponen Ben-Horin, et al, "Kinematics of a Three-Degree-Of-Freedom In-Parallel Actuated Manipulator Mechanism", Mech. Mach. Theory, 1997, 32(7), pp. 789-796.
[10] Ou Ma and Jorge Angeles, "Architecture Singularities of Parallel Manipulators" in International Journal of Robotics and Automation Design, 1983, 105:705-712.
[11] 孔令富．基于动力学的6-DOF并联机器人力补偿控制．机械工业自动化．1995(2)．
[12] Preundschuh G H, Stagger T G, and Kumar V. Design and Control of a 3-DOF In-Parallel Actuated Manipulator. J. of Rob. Sys., 1994,11(2): 103-115.
[13] 周凯．虚拟轴数控机床的虚实映射联动控制．中国机械工程，1998(3)．
[14] 周凯，陆建启．虚拟轴数控机床的仿三轴控制．组合机床于自动化加工技术．
[15] M. Honegger, A. Codoorey, E. Burget. Adaptive Control of the Hexaglide, a 6 dof Parallel
Manipulator. Proc. of the ICRA'97: 543-548.
[16] E. Burget, B. Sprenger, A. Codourey. Experiments in Nonlinear Adaptive Control. Proc. of the ICRA'97:537-542.
[17] 方浩，周冰等．基于层迭CMAC网络的6-DOF机器人自适应控制．机器人，2001，21(4)．
[18] 李迎等．虚拟轴机床的应用研究与发展趋势．机械设计与制造．1999，28(5)．
[19] H.V. Brussel et al. Robust Control of Feed Drive with Linear Motors. Annals of the CIRP, 1998，48(1).
[20] 汪劲松，黄田．并联机床—机床行业面临的机遇与挑战．中国机械工程，1999，10(10) 1103-1107．
[21] 黄真，孔令富，方跃法．并联机器人机构学理论及控制．北京，机械工业出版社，1997．12．
[22] M.Honegger, A.Codourey, and E.Burdet. Adaptive Control of the Hexaglide, a 6 dof Parallel Manipulator.[J]. in Proc.IEEE Int.Conf. Robotics and Automation, 1997, 543～548.
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