通用力反馈设备的自适应阻抗控制仿真研究

发布时间：2019-04-28 09:13

【摘要】：力反馈设备是一种人机交互设备,当操作者通过力反馈设备与虚拟环境进行交互时,力反馈设备能够提供虚拟环境的反馈力给操作者。操作者对力反馈设备进行操作时,操作者对力反馈设备施加的力可以通过测力装置来进行测量。若要对操作者与力反馈设备之间的力进行控制,则需要采用阻抗控制的方法。本文针对力反馈设备采用自适应阻抗控制方法进行控制仿真与研究。首先,介绍了力反馈设备的机械结构以及硬件部分的选型设计。对力反馈设备的驱动电机、关节传感器以及数据采集卡进行选型,并对其工作原理与性能进行研究。然后,对力反馈设备进行运动学与动力学分析。建立力反馈设备运动学方程,求解力反馈设备的雅各比矩阵,并且得到力反馈设备的工作空间。采用Matlab机器人工具箱进行仿真,验证运动学分析的正确性。采用拉格朗日法对力反馈设备进行动力学分析,通过编程来求解力反馈设备的动力学方程,为之后的自适应阻抗控制仿真做好了准备。接着,针对力反馈设备进行了自适应阻抗控制仿真,并对仿真结果进行分析。利用Matlab中的Simmechanics工具对力反馈设备进行建模,在Simulink环境下搭建了自适应阻抗控制系统,选取合适的阻抗控制参数M,K,B进行仿真。自适应阻抗控制具有不需要精确控制模型的优点,通过迭代的方法进行控制。通过仿真得到末端执行器的位移与力的跟踪曲线,分析仿真结果可以得出,自适应阻抗控制方法可以准确跟踪期望的阻抗力,具有较好的控制性能,并且对于外界环境的变化具有一定的鲁棒性。接着,采用模糊自整定的方法对阻抗控制参数M,K,B进行寻优。为了避免通过大量试用来确定阻抗控制参数,采用模糊自整定的方法对阻抗控制参数进行在线寻优,在仿真过程中,不断检测位置的误差及其变化率,制定模糊规则,通过模糊推理,最终进行解模糊来得到阻抗控制参数的最优值,节约了大量时间并且具有良好的控制效果。最后,采用基本的粒子群算法对阻抗控制M,K,B参数进行寻优。将阻抗参数作为粒子,建立适应度函数,通过不断的迭代计算来寻找最优粒子的位置,最终得到最优的阻抗控制参数。采用离线寻优所得到的最优阻抗控制参数进行系统仿真,具有良好的控制效果。
[Abstract]:Force feedback device is a kind of human-computer interactive equipment. When the operator interacts with the virtual environment through the force feedback device, the force feedback device can provide the feedback force of the virtual environment to the operator. When the operator operates the force feedback equipment, the force applied by the operator to the force feedback device can be measured by the force measuring device. In order to control the force between the operator and the force feedback equipment, impedance control method is needed. In this paper, the adaptive impedance control method is used to simulate and study the force feedback equipment. Firstly, the mechanical structure of the force feedback equipment and the selection design of the hardware part are introduced. The driving motor, joint sensor and data acquisition card of the force feedback device are selected, and its working principle and performance are studied. Then, the kinematics and dynamics of the force feedback equipment are analyzed. The kinematics equation of the force feedback equipment is established, the Yakubi matrix of the force feedback device is solved, and the workspace of the force feedback device is obtained. Matlab robot toolbox is used to simulate and verify the correctness of kinematics analysis. Lagrangian method is used to analyze the dynamics of the force feedback device, and the dynamic equation of the force feedback device is solved by programming, which is ready for the simulation of adaptive impedance control. Then, the adaptive impedance control simulation of the force feedback device is carried out, and the simulation results are analyzed. The force feedback equipment is modeled by the Simmechanics tool in Matlab, and the adaptive impedance control system is built in Simulink environment. The appropriate impedance control parameters M, K, B are selected for simulation. Adaptive impedance control has the advantage of no precise control model, and it is controlled by iterative method. The tracking curves of displacement and force of the end actuator are obtained by simulation. The simulation results show that the adaptive impedance control method can accurately track the desired resistance and has better control performance. And it is robust to the change of external environment. Then, fuzzy self-tuning method is used to optimize the impedance control parameters M, K, B. In order to avoid determining the impedance control parameters through a large number of trials, the fuzzy self-tuning method is used to optimize the impedance control parameters on-line. In the simulation process, the error of the position and its changing rate are constantly detected, and the fuzzy rules are formulated. The optimal value of impedance control parameters is obtained by fuzzy reasoning, which saves a lot of time and has a good control effect. Finally, the basic particle swarm optimization algorithm is used to optimize the impedance control parameters M, K, B. The impedance parameter is taken as the particle and the fitness function is established. The optimal position of the particle is found through continuous iterative calculation, and finally the optimal impedance control parameter is obtained. The optimal impedance control parameters obtained from off-line optimization are used to simulate the system, which has a good control effect.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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