Large-Scale Mechanical Vibration Compensation Algorithm Based on Six Degrees of Freedom Platform
DOI:
https://doi.org/10.71222/sp3r0w19Keywords:
six degree of freedom platform, vibration compensation, precision docking, model predictive control, robust controlAbstract
The harmful vibrations generated by large machinery during operation significantly impact processing accuracy and structural lifespan. This paper addresses this issue by proposing an active vibration compensation algorithm for high-voltage combined electrical equipment in precision docking scenarios, based on a six-degree-of-freedom platform. The study begins with the establishment of a comprehensive dynamic model of the Stewart platform to analyze the typical low-frequency vibration characteristics of large machinery. It then designs a composite control architecture that integrates feedforward and robust feedback. By real-time vibration signal acquisition, the platform generates inverse dynamic compensation commands using model predictive control, while introducing sliding mode control to enhance robustness against external disturbances. After verifying the algorithm's effectiveness in reducing vibration attenuation by over 90% at frequencies between 5 and 50Hz through simulations, a hydraulic-driven 6-DoF experimental platform was constructed to validate the system using a 10-ton simulated load. The experiments show that under diesel engine excitation conditions, the algorithm reduces the RMS value of key position errors by 82% and the peak vibration acceleration by 76%, significantly outperforming traditional PID control. This study provides an engineering solution for precise vibration suppression in large equipment.
References
1. Q. Gu, J. Tian, B. Yang, M. Liu, B. Gu, Z. Yin, L. Yin and W. Zheng, "A Novel Architecture of a Six Degrees of Freedom Parallel Platform," Electronics, vol. 12, no. 8, p. 1774, 2023, doi: 10.3390/electronics12081774.
2. Z. Chen, J. Song, N. Li et al., "Design and dynamics modeling of a novel 2R1T 3-DOF parallel motion simulator," J. Braz. Soc. Mech. Sci. Eng., vol. 45, p. 234, 2023, doi: 10.1007/s40430-023-04024-0.
3. H. Liu et al., "Deep learning-based multimodal control interface for human-robot collaboration," Procedia CIRP, vol. 72, pp. 3-8, 2018, doi: 10.1016/j.procir.2018.03.224.
4. H. Han, Y. Zhang, H. Zhang, C. Han, A. Li and Z. Xu, "Kinematic Analysis and Performance Test of a 6-DOF Parallel Plat-form with Dense Ball Shafting as a Revolute Joint," Appl. Sci., vol. 11, no. 14, p. 6268, 2021, doi: 10.3390/app11146268.
5. Z. Wang, Q. Gao, J. Xu and D. Li, "A Review of UAV Power Line Inspection," in Advances in Guidance, Navigation and Control, L. Yan, H. Duan and X. Yu, Eds., Lecture Notes in Electrical Engineering, vol. 644, Springer, Singapore, 2022. ISBN: 9789811581540.
6. M. Liu, Q. Gu, B. Yang, Z. Yin, S. Liu, L. Yin and W. Zheng, "Kinematics Model Optimization Algorithm for Six Degrees of Freedom Parallel Platform," Appl. Sci., vol. 13, no. 5, p. 3082, 2023, doi: 10.3390/app13053082.
