scholarly journals Research of Mechanical Resonance Analysis and Suppression Control Method of the Servo Drive System

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Wenli Li ◽  
Yongkang Liu ◽  
Shuaishuai Ge ◽  
Daming Liao

Transmission mechanisms of the servo drive system are not a pure rigid body, and the existence of the elastic transmission mechanisms will make the system generate mechanical resonance. Aiming at mechanical resonance of the servo drive system, the resonance generation mechanism is analyzed, the four-mass model considering the time-varying meshing stiffness of the gear is established, and the influence of different stiffness parameters on the mechanical resonance of the system is researched in this paper. The composite controller of Model Predictive Control (MPC) with Notch Filter is used to simulate the mechanical resonance suppression of the four-mass servo system considering time-varying meshing stiffness, and it is compared with the mechanical resonance suppression method based on Model Predictive Control. The simulation results show that when the step speed is 200 r/min, the overshoot is reduced from 11.6 r/min to 1.1 r/min, which is reduced by 90.5%. Under the impact load condition, from 10 Nm to 30 Nm, overshoot is reduced from 34.3 r/min to 12.8 r/min, reduced by 62%, and torque oscillation is reduced by 81.5%. Therefore, the composite controller of Model Predictive Control with Notch Filter can suppress the mechanical resonance problem effectively, caused by elastic transmission, and improve the robustness of servo drive system.

Author(s):  
Xiaohua Zeng ◽  
Liangyu Li ◽  
Dafeng Song ◽  
Lixin Li ◽  
Guanghan Li

A model predictive feedback control strategy based on time-varying efficiency is investigated and applied to a hydraulic hub-motor auxiliary system (HHMAS) in this paper. Adding HHMAS to a traditional heavy commercial vehicle can improve fuel economy and traction performance on roads with low adhesion coefficients. However, the hydraulic drive system experiences serious disturbance imposed by time-varying parameters and external conditions. Model predictive feedback control based on time-varying efficiency offers a solution for HHMAS to cope with the disadvantage of the hydraulic drive system and improve the environmental adaptability of the vehicle controller. In this study, the control law of hydraulic variable pump (HVP) target displacement is established based on temperature compensation in consideration of the influence of multiple factors on pump target displacement. For coordinated power distribution of HHMAS, the minimum wheel speed difference and the reduction in system impact are regarded as optimal control targets in adjusting the engine torque and HVP displacement and designing the model predictive controller. Simulation results show that the proposed model predictive control method can reduce the speed difference between front and rear wheels by up to 64% and can achieve the wheel speed following effect faster than the traditional proportional-integral-derivative algorithm. Given that the control parameters do not need to be calibrated in the proposed method, the calibration time is saved, and the actual development process of the hydraulic hub-motor driving vehicle is remarkably improved.


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