1. Adaptive rearrangement of actuator layout for the cable-driven vibration control of a membrane antenna.
- Author
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Shao, Qi, Lu, Yifan, Wang, Dan, Yue, Honghao, Chng, Chin-Boon, and Chui, Chee-Kong
- Subjects
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ANTENNAS (Electronics) , *ACTUATORS , *PLANT microtubules , *BIOLOGICALLY inspired computing , *ADAPTIVE control systems , *ENERGY transfer - Abstract
Although various studies on vibration control schemes exist, most of them focus on a one-time optimization of actuator layout. However, numerical results indicate significant drawbacks of fixed layouts on control performance, a factor rarely mentioned in the field of vibration control. This study aims to address this gap by proposing a novel rearrangement strategy that adaptively varies the actuator layout based on the vibration intensity pattern. The inspiration for this approach comes from the reorientation of cortical microtubules in plant cells, which adapt to stress patterns. The study first derives the definitions of vibration patterns and the index of intensity based on energy transfer. These definitions then guide the optimization of actuator layout throughout the control process. The study compares the fixed layout with the proposed adaptive varying layout, considering both full-state feedback and recognition feedback. The numerical results demonstrate that the proposed adaptive rearrangement of actuator layout significantly improves suppression performance, leading to higher utilization efficiency of control forces. Additionally, the presented strategy is tolerant to computation errors from recognition feedback, resulting in robust enhancements in vibration attenuation. Our study has introduced new possibilities for improving existing control schemes. • First-time practical dynamic rearrangement strategy adapts actuator layout based on system responses. • A bioinspired optimization framework aligns the actuator layout with a vibration intensity pattern in a fast-computing manner. • The strategy is compatible with both full-state feedback and recognition reconstructed from sensing signals. • Simulations show improved control performance with increased force utilization and error tolerance. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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