基于数据fcm聚类的移动机器人关节横摆力矩振动控制系统设计

摘要:

对于实际空间移动机器人，其运动涉及到复杂的多体动力学耦合关系，且不同部位关节间皆存在弹性影响，导致关节极易出现横摆振动。传统方法通常应用关节独立力反馈实现模态空间振动控制，但是由于机器人关节横摆力矩的变化范围较大，振动信号波动频率高，尤其在机器人不稳定移动状态下，独立提取每一个关节的振动特征难度极高，导致对机器人关节振动幅值的控制效果不明显。因此，设计基于模糊C均值聚类算法（fuzzy c-means algorithm，FCM）聚类的移动机器人关节横摆力矩振动控制系统。硬件方面，利用力矩传感器检测移动机器人关节横摆力矩，运用CPU+FPGA结构，设计一个集成了灵活逻辑控制、复杂通信协议支持的关节控制器硬件。软件方面，，通过聚合经验模态分解提取采集到的机器人关节横摆力矩振动信号特征，再引入数据FCM聚类算法识别关节振动模式，确定具体振动控制要求。结合PD（比例微分）控制器和LQR（线性二次型调节器）控制结构，建立联合控制策略。并考虑关节力矩反馈和电机位置误差，实现关节横摆力矩振动的最终控制。测试结果表明：针对移动机器人的左前腿关节的低频振动，该系统应用后，发生振动的关节最大振动减弱到0.22°，有效确保了移动机器人运行的稳定性。

Abstract:

For actual space mobile robots, their movements involve complex multi-body dynamics coupling relationships, and there are elastic effects between joints in different parts, which can easily lead to lateral vibration of joints. Traditional methods typically use joint independent force feedback to achieve modal space vibration control. However, due to the large range of changes in robot joint yaw moment and high frequency of vibration signal fluctuations, especially in unstable robot movement states, it is extremely difficult to independently extract the vibration characteristics of each joint, resulting in unclear control effect on the vibration amplitude of robot joints. Therefore, design a mobile robot joint yaw moment vibration control system based on fuzzy c-means algorithm (FCM) clustering. In terms of hardware, a torque sensor is used to detect the lateral swing torque of mobile robot joints, and a joint controller hardware that integrates flexible logic control and complex communication protocol support is designed using a CPU+FPGA structure. In terms of software, the collected robot joint lateral torque vibration signal features are extracted by aggregating empirical mode decomposition, and then the data FCM clustering algorithm is introduced to identify joint vibration patterns and determine specific vibration control requirements. Establish a joint control strategy by combining PD (proportional derivative) controller and LQR (linear quadratic regulator) control structure. And considering joint torque feedback and motor position error, achieve the final control of joint lateral torque vibration. The test results show that for the low-frequency vibration of the left front leg joint of the mobile robot, after the application of this system, the maximum vibration of the joint that vibrates is reduced to 0.22 °, effectively ensuring the stability of the mobile robot"s operation.Regarding the problem of joint lateral torque vibration in mobile robots, the joint vibration control is mainly based on the sliding mode control idea, which relies on fixed control parameters and models, resulting in a relatively large joint vibration amplitude after system control. Therefore, a mobile robot joint yaw moment vibration control system based on data FCM (fuzzy C-means) clustering is proposed. In terms of hardware, the basic structure and circuit optimization design have been completed for the two core hardware devices of torque sensors and joint controllers. In terms of software, a dynamic model is established based on the joint motion principle of mobile robots. Collect the lateral torque vibration signals of robot joints, extract vibration features through empirical mode decomposition, and then introduce data FCM clustering algorithm to identify joint vibration patterns and determine specific vibration control requirements. Establish a joint control strategy by combining PD (proportional derivative) controller and LQR (linear quadratic regulator) control structure. And considering joint torque feedback and motor position error, achieve the final control of joint lateral torque vibration. The test results show that after the application of the control system, the maximum amplitude of the robot joint vibration is reduced to 0.22 °, ensuring the stability of the mobile robot operation.