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网络遥操作机器人采样系统模型与控制研究
Alternative TitleStudy of Model and Control of Network-Based Teleoperation Robot Sampling Systems
符秀辉1,2
Department机器人学研究室
Thesis Advisor王越超
ClassificationTP242
Keyword网络遥操作 采样控制 网络延时 肌肉模型 切换控制
Call NumberTP242/F82/2009
Pages107页
Degree Discipline模式识别与智能系统
Degree Name博士
2009-02-14
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Abstract网络遥操作机器人系统是网络技术与机器人技术相结合的产物。它延伸了操作者的感知和操作能力,使操作者可以置身于安全的环境中而完成危险环境中的作业任务;提高了机器人对工作环境的适应能力,辅之以操作者的决策,机器人可以工作于非结构化的工作环境中。网络遥操作机器人技术作为机器人学的一个重要分支,近十几年来受到许多研究机构和研究人员的关注和重视。本文针对网络遥操作机器人采样控制结构,通过控制策略解决非结构环境下网络遥操作机器人的实时控制问题。为此,首先研究了网络遥操作机器人采样系统建模问题。目前,关于网络遥操作机器人采样系统模型大多是针对单采样周期的,主从端不同采样周期的统一模型目前还没有相关报道。由于操作者是网络遥操作机器人采样系统的组成部分,因此若建立网络遥操作机器人采样系统模型首先要建立操作者模型。然而由于操作者建模问题比较复杂,目前在遥操作系统建模时,一般都避开了操作者建模问题。本文在分析了现有的遥操作控制方式和遥操作系统模型的基础上,主要针对网络遥操作机器人采样系统模型和控制问题进行研究。操作者模型研究方面,主要以操作者用小臂操作具有力反馈功能的操纵杆为例,研究操作者操作操纵杆过程的动态模型建模方法。首先对人体骨骼肌肌肉力学模型中不可测量,即肌肉激活度,通过实验进行研究,得出在操作者保持紧张程度不变情况下“肌肉激活度”与肌肉收缩长度的关系。在此基础上,考虑手臂的动力学特性、操纵杆的动力学特性,建立了肌肉力驱动的手臂—操纵杆系统动力学模型。在操作者模型的基础上,设计动态补偿器,补偿操作者操作操纵杆的动态过程,解决由于肌肉动态特性被污染所造成的操作者所想与所做不一致的问题,克服操作者操作时延,提高网络遥操作机器人系统的性能。遥操作机器人采样系统模型研究方面,首先针对主从端不同采样周期的网络遥操作机器人采样控制结构,通过引入双端口RAM的方法,实现网络遥操作机器人系统主从端的采样同步;在网络遥操作机器人采样同步控制结构模型的基础上,建立从端离散状态空间表达式,利用提升技术对从端离散状态空间表达式按遥操作周期提升,利用采样系统理论得到主从端统一的网络遥操作机器人采样系统模型;最后对从端系统提升前后的稳定性、可控性、可观测性进行分析,得出从端系统提升前后稳定性、可控性、可观测性不变的结论。遥操作控制策略研究方面,提出基于时延预测的采样切换控制方法。首先对互联网节点间的网络时延进行测试分析,得出任意两个网络节点间时延分布规律,即任意时间段内网络时延的概率密度都可以用平移Gamma分布曲线描述。采用拟合样本概率密度曲线的方法,对平移Gamma参数进行预估,得出平移Gamma分布的种类,进而根据平移Gamma分布的种类,确定出网络时延的均值,最后确定出期望的采样周期;为了实现任意采样周期下切换系统的稳定控制,对采样切换系统的稳定性进行了研究,得到如下结论,即如果从端系统一致渐进稳定,则对从端实行任意采样切换控制时网络遥操作机器人采样系统是稳定的。为了对所研究内容进行实验验证,以移动机器人为被控对象,搭建了一个具有力反馈控制和局部自主功能的网络遥操作机器人采样系统实验平台。用人工势场法建立了虚拟力模型并给出了虚拟力在力反馈操纵杆上的实现方法;以移动机器人自主避障为例,给出了从端自主的模糊控制设计方法和实验系统遥操作软件设计方法。实验结果证明了所提出的模型和控制方法是有效的、可行的,对于建立性能良好的网络遥操作机器人系统具有现实意义。本文所研究的许多结论,对于一般网络遥操作机器人系统的理论研究和实际应用也具有一定的参考价值。
Other AbstractNetwork-based teleoperation robot system is the product of the combination network technology and robot technology. It extends the operators' perception and operational capabilities, so that the operators will be able to stay in a safe environment to complete dangerous tasks. The adaptability to the work environment of the robot is also improved, with the operators’ decision-making, the robot can work in unstructured work environment. Network teleoperation robot technology as an important branch of robotics, over the past decade, it received many research institutions and researchers’ concern and attention. In allusion to the construction of network-based teleoperation robot, this paper resolved the issue of real-time control through the control strategy in the unstructured environment. It first researched the modeling problem of the network-based teleoperation robot sampling systems. At present, the most models of the network-based robot sampling systems are for a single sampling period, the report about unified model of master-salve end for different sampling period hasn’t appeared yet. Operator as an integral part of the sampling system, the model of it should be first established. However, due to the modeling problem of operator is rather complicated, the current modeling of teleoperation control system generally avoids the modeling problem of operator. The main researches of this paper are the model and control problem of the network-based teleoperation robot sampling systems. In the research of the operator model, the operator’s forearm was used to manipulate the joystick with force feedback. It studied its dynamic modeling method that the operator manipulated the joystick. First, through experimental research of the muscle activation degree which is immeasurable in the muscle strength model, we concluded that the muscle activation degree is in proportion to the length and velocity of muscle in the case that the nervous degree of operator was constant. Then, considered to the dynamics characteristic of forearm and joystick, the forearm-joystick dynamic model driven by muscle strength was established. Finally, we designed the compensator which was used to resolve the inconsistency problem about what the operators want and what they do. It overcomes the time delay of operation and improves performances of network-based teleoperation systems. In the research of robot sampling systems, in allusion to different sampling control construction of master-salve end for different sampling period, we achieved master-salve synchronization of the teleoperation systems by introducing hardware dual RAM. On the basis of construct model of sampling synchronization control, the discrete state space expression can be established, and then control system of the slave-end robot was lift according to the teleoperation cycle by using lift technique. The unified model of sampling control systems of network-based teleoperation robot was received through the combination of master-end model and slave-end model lifted. Finally, it came to the conclusion that the stability, the state controllability and observability are invariability before and after slave-end lifted by analyzing controllability and observability of the systems. In the research of teleoperation control decision-making, the method of sampling switch control which is based on prediction of time delay was given. First, the internet time delay between two internet-nodes was tested and analyzed. Namely, the probability density of the network time delay in any time period can be described by parallel moving Gamma curve. The category of parallel moving Gamma can be received after estimating the parallel moving Gamma parameters using the method of fitting the sample probability density curve. The average of the network delay also can be determined according to the category of parallel moving Gamma. So that we can determine the expected sampling period. In order to achieve stability control of the systems when switch happened in arbitrary sampling period, the stability of sampling switch system have been studied, and received following conclusion. If slave-end system is uniformly asymptotical stability, the network-based teleoperation robot sampling systems are stable when arbitrary sampling switch control is implemented to the slave - end. Taken mobile robot as the controlled object, we carried on the experimental verification. a sampling control experimental platform of network-based teleoperation robot with force feedback and local autonomy was established. Virtual force model was established by using method of artificial potential field and implementation of the virtual force of the joystick with force reflection was given out. Taken autonomous obstacle avoidance of mobile robot as an example, it raised a fuzzy control design method of slave-end autonomy, and introduced the software design of sampling control experimental system. Experimental results show that the proposed model and control method is effective, feasible and significant to the establishment of good network teleoperation robot systems. The conclusions of sampling control systems of network-based teleoperation robot researched in this paper have referenced value for theory study and practical application of general internet control system.
Language中文
Contribution Rank1
Document Type学位论文
Identifierhttp://ir.sia.cn/handle/173321/114
Collection机器人学研究室
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院研究生院
Recommended Citation
GB/T 7714
符秀辉. 网络遥操作机器人采样系统模型与控制研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2009.
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