Piezoelectric actuators frequently exhibit a time-dependent behavioral phenomenon known as hysteresis, resulting in a lag in the deformation of the actuator compared to linear models. The presence of hysteresis complicates control systems involving piezoelectric actuators. However, traditional modeling methods for piezoelectric actuated smart structures often treat the piezoelectric patches as linear actuators without considering hysteresis, leading to suboptimal controller performance.
This thesis aims to establish a comprehensive model by integrating the Euler-Bernoulli beam bending model with the hysteresis dynamics induced by two opposing piezoelectric patches attached to a beam. A model expansion method is employed to transform the partial differential equations describing beam vibration into a set of ordinary differential equations in the modal coordinate frame. These equations are then coupled with the Bouc-Wen model describing the hysteresis of piezoelectric materials.
Model parameters are identified using a genetic algorithm tested against experimental data across varied excitation frequencies. The experimental dataset is divided into two sets: a training set for the genetic algorithm and a validation set to verify the identified model. Results demonstrate that the inclusion of hysteresis in a nonlinear model provides better agreement with experimental results than the linear model, thereby enhancing the predictive capability of piezoelectric actuator behavior. This thesis has laid the foundation for future work on advanced control methods to mitigate beam vibration under external excitation, thus optimizing smart structure performance.
| Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-4457 |
| Date | 01 June 2024 |
| Creators | Maas, Andrew Donald |
| Publisher | DigitalCommons@CalPoly |
| Source Sets | California Polytechnic State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Master's Theses |
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