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.
