Chengdu Academy of Agriculture and Forestry Sciences, Chengdu, Sichuan, People's Republic of China.
Sci Prog. 2021 Jan-Mar;104(1):368504211003383. doi: 10.1177/00368504211003383.
In order to solve the problem of poor robustness of the traditional method of calculating torque in the mechanical model of 7-DOF picking manipulator, this paper proposes a control strategy of calculating torque plus fuzzy compensation by using adaptive fuzzy logic system to compensate the uncertain part of the mechanical model of 7-DOF picking manipulator. By using Lagrange method, the dynamic model of 7-DOF manipulator is established, and the relationship between joint motion and applied torque (force) is obtained. Using ADAMS and MATLAB to establish a co-simulation platform, the manipulator and trajectory tracking control system are simulated. The results show that the trajectory tracking error of each joint in the algorithm is obviously reduced and the convergence trend is obvious. The average trajectory tracking accuracy of joint 1 to joint 7 was improved by 70.22%, 94.78%, 0.62%, 74.23%, 89.78%, 86.45%, and 67.15%, respectively. In this control scheme, the control force (moment) of each joint changes regularly, and the output force (moment) does not appear chattering and mutation when the disturbance signal is added. The research results can provide support for the further study of picking manipulator trajectory tracking control system.
为了解决 7-DOF 采摘机械手机械模型中传统扭矩计算方法鲁棒性差的问题，本文提出了一种基于自适应模糊逻辑系统的扭矩计算加模糊补偿的控制策略，利用自适应模糊逻辑系统补偿 7-DOF 采摘机械手机械模型的不确定部分。通过拉格朗日方法建立了 7-DOF 机械手的动力学模型，得到了关节运动与施加扭矩（力）之间的关系。利用 ADAMS 和 MATLAB 建立了联合仿真平台，对机械手和轨迹跟踪控制系统进行了仿真。结果表明，该算法中各关节的轨迹跟踪误差明显减小，收敛趋势明显。关节 1 到关节 7 的平均轨迹跟踪精度分别提高了 70.22%、94.78%、0.62%、74.23%、89.78%、86.45%和 67.15%。在该控制方案中，各关节的控制力（力矩）呈周期性变化，在加入干扰信号时，输出力（力矩）不会出现抖动和突变。研究结果可为进一步研究采摘机械手轨迹跟踪控制系统提供支持。
