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With the development of robot technology, integrated joints with small volume and convenient installation have been widely used. Based on the double inertia system, an integrated joint motor servo system model considering gear angle error and friction interference is established, and a joint control strategy based on BP neural network and pole assignment method is designed to suppress the vibration of the system. Firstly, the dynamic equation of a planetary gear system is derived based on the Lagrange method, and the gear vibration of angular displacement is calculated. Secondly, the vibration displacement of the sun gear is introduced into the motor servo system in the form of the gear angle error, and the double inertia system model including angle error and friction torque is established. Then, the PI controller parameters are determined by pole assignment method, and the PI parameters are adjusted in real time based on the BP neural network, which effectively suppresses the vibration of the system. Finally, the effects of friction torque, pole damping coefficient and control strategy on the system response and the effectiveness of vibration suppression are analyzed. [ABSTRACT FROM AUTHOR]

To study the vibration characteristics of deep-groove ball bearing, considering the influence of sliding, the dynamic model of the DGB 6205 system is established in this paper. The DGB 6205 system model includes the movement of the bearing inner ring in the X and Y directions, the rotation of the cage, the rotation movement of each ball, the revolution movement of each ball and the movement along the radial direction of each ball. Based on the system model, the differential equations of motion of the system are established, and the correctness of the model is verified by experiment. The slip characteristics of the DGB 6205 system are studied by numerical simulation. At the same time, the influence of time-varying load on the vibration characteristics of the system is studied. Then, the sensitivity of system parameters is analyzed. The results show that the sliding speed between the ball and the inner raceway is greater than that between the ball and the outer raceway. The radial vibration response of DGB 6205 system under time-varying load is less than that under constant load. The increase of radial clearance will increase the vibration response of DGB 6205 system. [ABSTRACT FROM AUTHOR]

The "inerter-spring-damper" (ISD) suspension system is a suspension system composed of an inerter, spring, and damper. To study the ride comfort and stability of the vehicle by using the ISD suspension system, a vehicle model with ISD suspension is established in this paper. The vehicle model including vertical, pitch, roll, and yaw motion of the vehicle body. Based on the vehicle model, the differential equation of motion with ISD suspension is obtained. The dynamic responses of the ISD suspension system are investigated by using different road excitations. At the same time, the influence of coupled excitation and single excitation on the vibration reduction performance of the ISD suspension system is studied. Then, the dynamic responses of ISD suspension and passive suspension are compared, and the improvement of comprehensive vibration reduction performance of ISD suspension system is quantitatively analyzed. The numerical results illustrate the ISD suspension has the optimal vehicle speed under different road excitations, and the comprehensive vibration reduction performance of the ISD suspension is the best when driving at the optimal vehicle speed. Under different types of road excitation, ISD suspension shows excellent comprehensive vibration reduction performance. ISD suspension is more suitable for vibration reduction of complex roads than that of a single road. [ABSTRACT FROM AUTHOR]

Gravity and flexibility will cause fluctuations of the rotation angle in the servo system for flexible manipulators. The fluctuation will seriously affect the motion accuracy of end-effectors. Therefore, this paper adopts a control method combining the RBF (Radial Basis Function) neural network and pole placement strategy to suppress the rotation angle fluctuations. The RBF neural network is used to identify uncertain items caused by the manipulator's flexibility and the time-varying characteristics of dynamic parameters. Besides, the pole placement strategy is used to optimize the PD (Proportional Differential) controller's parameters to improve the response speed and stability. Firstly, a dynamic model of flexible manipulators considering gravity is established based on the assumed mode method and Lagrange's principle. Then, the system's control characteristics are analyzed, and the pole placement strategy optimizes the parameters of the PD controllers. Next, the control method based on the RBF neural network is proposed, and the Lyapunov stability theory demonstrates stability. Finally, numerical analysis and control experiments prove the effectiveness of the control method proposed in this paper. The means and standard deviations of rotation angle error are reduced by the control method. The results show that the control method can effectively reduce the rotation angle error and improve motion accuracy. [ABSTRACT FROM AUTHOR]