Sun, H., & Ge, S. S. (2025). Geometry Analysis and Experimental Study for Vibration Damping of Rectangular Plate. IEEE/ASME Transactions on Mechatronics, 1–12. https://doi.org/10.1109/tmech.2025.3626951
Abstract:
The effectiveness of vibration damping in rectangular plates depends not only on the control strategy but also on the geometric layout of the actuators. This study proposes a control-integrated geometry selection strategy that directly incorporates closed-loop control behavior. The geometry of cable-driven robots is analyzed by determining the number of cables required and identifying the positions of anchor points on the plate. A performance evaluation index is introduced, which simultaneously considers stabilization time, maximum cable force, and the number of cables. The selection strategy can provide optimized results tailored to diverse objectives, such as shorter stabilization time, reduced cable force, or fewer cables. Drawing on the patterns of the control input of the designed deep reinforcement learning-based controller, a new control law with customizable functions is developed, allowing for flexible output force modulation. It addresses the highly irregular nature of reinforcement learning-based control inputs and enhances the practicality in real-world applications. By combining the proposed control law with the geometry selection strategy, this study examines the effect of different geometric layouts on vibration damping in a rectangular plate under two distinct boundary conditions. A six-meter-scale experimental platform is constructed to assess sixteen geometric layouts under these two boundary conditions. Simulation and experimental results validate the practical feasibility of the geometry selection strategy for improving the vibration-damping effect in rectangular plates.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A*STAR - Singapore RIE2025 Manufacturing, Trade and Connectivity (MTC) Industry Alignment Fund–Pre-Positioning (IAF-PP)
Grant Reference no. : M22K4a0044
This research / project is supported by the Ministry of Education - Ministry of Education, Singapore Research Centre of Excellence Institute for Functional Intelligent Materials
Grant Reference no. : EDUNC-33-18-279-V12