二自由度机械臂建模与控制研究

发布时间：2018-04-23 00:31

本文选题：自适应控制 + 遥操作　；参考：《昆明理工大学》2017年硕士论文

【摘要】：近年来,由于人口红利流失,中国积极主导经济发展转型,境内劳力密集的低端制造业正逐渐转型为技术密集的高端制造业,因此高度自动化的需求水涨船高,带动工业机器人研发水平快速成长。随着机器人产业的不断发展,人们对机器人的性能需求也越来越高,研究机器人的控制问题已经成为解决机器人轨迹精度不精确的有效方法并逐渐成为研究热点。本课题对机器人的运动控制算法进行了深入研究,分别将自适应控制策略和未知输入观测器应用于机器人这种典型的非线性系统上,针对不同应用场景分别提出了三种控制策略:(1)单机械臂的鲁棒自适应控制。通过引入滤波变换和在自适应律中引入泄漏项,提出了保证参数估计的机械臂鲁棒自适应控制方法。分析证明了该算法可以实现参数误差和追踪误差的同时收敛,且具有较强的鲁棒性。(2)双边遥操作系统的鲁棒自适应控制。将所提出的单机械臂自适应控制方法拓展到双边遥操作系统,提出了保证参数估计的双边遥操作机械臂鲁棒自适应控制算法。分析证明所提控制策略可以保证系统在通讯延迟的情况下实现参数误差收敛以及主从状态跟随。(3)基于未知输入观测器的机械臂运动控制。通过引入滤波变换,设计未知输入观测器观测外部干扰及未建模动态,并将观测出来的估计值作为控制器前馈预补偿干扰及未建模动态造成的影响。该控制方法的控制设计及调参十分简单使用,并且能有效抵抗外部干扰,具有较强的鲁棒性。在完成上述理论研究的同时,本课题还进行了仿真分析,通过与传统控制方法比较验证了所提算法的优势。最后,本课题以自行研制的SCARA(Selective Compliance Assembly Robot Arm选择顺应性装配机械臂)机器人为研究对象,应用所提出的控制算法对其进行实验。实验结果验证了所提算法在实际工程应用中的有效性。
[Abstract]:In recent years, as a result of the loss of the population dividend, China has actively led the transformation of economic development, and the labor-intensive low-end manufacturing industry in China is gradually transforming into a technology-intensive high-end manufacturing industry. As a result, the demand for high automation is rising. Drive industrial robot R & D level to grow rapidly. With the development of robot industry, the demand for robot performance is becoming higher and higher. The research on robot control has become an effective method to solve the inaccurate trajectory accuracy of robot and has gradually become a research hotspot. In this paper, the motion control algorithm of the robot is deeply studied, and the adaptive control strategy and the unknown input observer are applied to the typical nonlinear system of the robot. For different application scenarios, robust adaptive control of single manipulator with three control strategies: 1) is proposed. By introducing the filter transform and the leakage term into the adaptive law, a robust adaptive control method for the manipulator is proposed, which guarantees the estimation of the parameters. It is proved that the proposed algorithm can converge at the same time as the parameter error and the tracking error, and has strong robustness. 2) robust adaptive control of the bilateral teleoperation system. The proposed adaptive control method for single manipulator is extended to the bilateral teleoperation system, and a robust adaptive control algorithm for the two-sided telemanipulator is proposed to guarantee parameter estimation. It is proved that the proposed control strategy can guarantee the convergence of the parameter error and the master-slave state following. 3) the manipulator motion control based on the unknown input observer can be guaranteed by the proposed control strategy. The unknown input observer is designed to observe the external disturbance and the unmodeled dynamic by introducing the filter transform, and the estimated values are taken as the influence of the feedforward disturbance and the unmodeled dynamic of the controller. The control design and parameter adjustment of the control method are very simple to use, and can effectively resist external interference, and have strong robustness. At the same time, the simulation analysis is carried out, and the advantages of the proposed algorithm are verified by comparing with the traditional control methods. Finally, the self-developed SCARA(Selective Compliance Assembly Robot Arm (SCARA(Selective Compliance Assembly Robot Arm) robot is used as the research object, and the proposed control algorithm is used to test the robot. Experimental results verify the effectiveness of the proposed algorithm in practical engineering applications.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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