The simultaneous measurement/electrical actuation of piezoelectric elements has been a subject of considerable interest in previous research. Within a limited bandwidth, piezoelectric materials can be modeled electrically as a voltage source and capacitor in series and when these components are integrated into a balanced capacitive bridge, simultaneous actuation and strain sensing is possible. Unfortunately, due to the sensitivity of piezoelectric materials to changing environmental conditions (temperature) and applied voltages, an adaptive scheme is required to maintain a balanced bridge and reduce high voltage spillover into the measurement channel. Even minute changes in the piezoelectric capacitance can overwhelm the strain sensing signal with high voltage content thereby preventing accurate strain sensing. The purpose of this work is to apply the self-sensing algorithm to a flexible structure with piezoelectric sensors/actuators mounted to its surface. The flexible structure utilized in this paper is composed of a small, cantilever resonator beam with two piezoelectric patches integrated into its structure and this beam is mounted at a arbitrary location to a larger, primary cantilever beam. The first two resonances of the actuator beam were tuned to that of the primary beam. High voltage signals are applied to the patch near the root of the resonator beam and simultaneous strain-induced voltage sensing is performed. Simulations have shown that estimation performance degrades with increasing rates of piezoelectric capacitance variation and conversely, adaptation times were found to decrease with increasing adaptive gains over the limited ranges of gains applied.
- Dynamic Systems and Control Division
Adaptive Piezoelectric Self-Sensing Performance for Varying Piezoelectric Capacitance and Adaptation Gain
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Lundstrom, T, & Jalili, N. "Adaptive Piezoelectric Self-Sensing Performance for Varying Piezoelectric Capacitance and Adaptation Gain." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 1: Aerospace Applications; Advances in Control Design Methods; Bio Engineering Applications; Advances in Non-Linear Control; Adaptive and Intelligent Systems Control; Advances in Wind Energy Systems; Advances in Robotics; Assistive and Rehabilitation Robotics; Biomedical and Neural Systems Modeling, Diagnostics, and Control; Bio-Mechatronics and Physical Human Robot; Advanced Driver Assistance Systems and Autonomous Vehicles; Automotive Systems. Tysons, Virginia, USA. October 11–13, 2017. V001T15A005. ASME. https://doi.org/10.1115/DSCC2017-5192
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