An Intelligent Piezoelectric System Integrating Self‐Sensing and Autonomous Operation for Adaptive Vibration Control

Smart structures operating under varying dynamic environments require vibration control systems that can maintain effective damping while remaining compact for practical deployment. Synchronized switching damping (SSD), a semi‐active vibration control technique, is attractive for this application purpose because of its compactness, broad operational bandwidth, and low power consumption. However, existing SSD systems strongly rely on auxiliary instrumentation, increasing system complexity and limiting their practical deployment. In this study, we present an intelligent SSD system implemented within a unified architecture. By integrating a peak‐detection module, a switching module, and an adaptive bias‐flip SSD interface, the proposed system can autonomously identify vibration states, determine switching timing, and adaptively adjust its damping behavior. Experimental results demonstrate that, under an excitation of 0.05 g at 11.98 Hz, the system reduces the vibration amplitude by 75.5% relative to the uncontrolled case and achieves a further 20.7% reduction compared to the SSD on inductor (SSDI) technique. Furthermore, the proposed system achieves vibration suppression comparable to the SSD on voltage source (SSDV) at moderate bias voltages, while maintaining its high adaptive capability. These results establish the proposed system as a practical, integrated solution for autonomous, adaptive piezoelectric vibration control in smart structures under varying dynamic conditions.

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Publication Details

Journal
Advanced Intelligent Systems
Published
2026-09-11
DOI
https://doi.org/10.1002/aisy.70539
Primary Topic
Aeroelasticity and Vibration Control
Type
article
Field-Weighted Citation Impact
0.00
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An Intelligent Piezoelectric System Integrating Self‐Sensing and Autonomous Operation for Adaptive Vibration Control

Guobiao Hu, Weiqun Liu, Hao Tang
Advanced Intelligent Systems
Aeroelasticity and Vibration Control
article

An Intelligent Piezoelectric System Integrating Self‐Sensing and Autonomous Operation for Adaptive Vibration Control

Guobiao Hu, Weiqun Liu, Hao Tang
article en

Abstract

Smart structures operating under varying dynamic environments require vibration control systems that can maintain effective damping while remaining compact for practical deployment. Synchronized switching damping (SSD), a semi‐active vibration control technique, is attractive for this application purpose because of its compactness, broad operational bandwidth, and low power consumption. However, existing SSD systems strongly rely on auxiliary instrumentation, increasing system complexity and limiting their practical deployment. In this study, we present an intelligent SSD system implemented within a unified architecture. By integrating a peak‐detection module, a switching module, and an adaptive bias‐flip SSD interface, the proposed system can autonomously identify vibration states, determine switching timing, and adaptively adjust its damping behavior. Experimental results demonstrate that, under an excitation of 0.05 g at 11.98 Hz, the system reduces the vibration amplitude by 75.5% relative to the uncontrolled case and achieves a further 20.7% reduction compared to the SSD on inductor (SSDI) technique. Furthermore, the proposed system achieves vibration suppression comparable to the SSD on voltage source (SSDV) at moderate bias voltages, while maintaining its high adaptive capability. These results establish the proposed system as a practical, integrated solution for autonomous, adaptive piezoelectric vibration control in smart structures under varying dynamic conditions.

Advanced Intelligent Systems
Southwest Jiaotong University (CN), University of Hong Kong (HK), South China University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 7%
Aeroelasticity and Vibration Control
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An Intelligent Piezoelectric System Integrating Self‐Sensing and Autonomous Operation for Adaptive Vibration Control — Guobiao Hu, Weiqun Liu, et al. · Advanced Intelligent Systems (2026) | TGRS Research Map | TGRS