@article{bravo_smith_2019, title={Parameter-dependent Surrogate Model Development for PZT Bimorph Actuators Employed for Micro-air Vehicles}, volume={10968}, ISSN={["1996-756X"]}, DOI={10.1117/12.2514246}, abstractNote={In the paper, we discuss the use of the homogenized energy model (HEM) to develop a dynamic mode decomposition surrogate model for a PZT bimorph actuator used for micro-air vehicles including Robobee. The HEM quantifies the nonlinear, hysteretic, and rate-dependent behavior inherent to PZT in highly dynamic operating regimes. Due to the computation complexity of the HEM, we must develop a surrogate model. The surrogate model must be parameter- and control-dependent to be able to perform inverse problems or uncertainty quantification in different driving regimes. In the literature, DMD can be adapted to address different control inputs. We will discuss using interpolation over the parameters to adapt the DMD to include parameter dependence. Finally, we will discuss the results and limitations of the new surrogate model.}, journal={BEHAVIOR AND MECHANICS OF MULTIFUNCTIONAL MATERIALS XIII}, author={Bravo, Nikolas and Smith, Ralph C.}, year={2019} }
 @article{bravo_smith_crews_2018, title={Uncertainty Quantification for PZT Bimorph Actuators}, volume={10596}, ISSN={["1996-756X"]}, DOI={10.1117/12.2297148}, abstractNote={In this paper, we discuss the development of a high fidelity model for a PZT bimorph actuator used for micro-air vehicles, which includes the Robobee. We developed a high-fidelity model for the actuator using the homogenized energy model (HEM) framework, which quantifies the nonlinear, hysteretic, and rate-dependent behavior inherent to PZT in dynamic operating regimes. We then discussed an inverse problem on the model. We included local and global sensitivity analysis of the parameters in the high-fidelity model. Finally, we will discuss the results of Bayesian inference and uncertainty quantification on the HEM.}, journal={BEHAVIOR AND MECHANICS OF MULTIFUNCTIONAL MATERIALS AND COMPOSITES XII}, author={Bravo, Nikolas and Smith, Ralph C. and Crews, John}, year={2018} }
 @inproceedings{bravo_smith_crews_2017, title={Data-driven model development and feedback control design for PZT bimorph actuators}, DOI={10.1115/smasis2017-3847}, abstractNote={In the paper, we discuss the development of a high-fidelity and surrogate model for a PZT bimorph used as an actuator for micro-air vehicles including Robobee. The models must quantify the nonlinear, hysteretic, and rate-dependent behavior inherent to PZT in dynamic operating regimes. The actuator dynamics are initially modeled using the homogenized energy model (HEM) framework. This provides a comprehensive high-fidelity model, which can be inverted and implemented in real time for certain control regimes. To improve efficiency, we additionally discuss the development of data-driven models and focus on the implementation of a surrogate model based on a dynamic mode decomposition (DMD). Finally, we detail the design and implementation of a PI controller on the surrogate and high-fidelity models.}, booktitle={Proceedings of the asme conference on smart materials adaptive}, author={Bravo, N. and Smith, Ralph and Crews, J.}, year={2017} }
 @article{bravo_smith_crews_2017, title={Surrogate Model Development and Feedforward Control Implementation for PZT Bimorph Actuators Employed for Robobee}, volume={10165}, ISSN={["1996-756X"]}, DOI={10.1117/12.2259948}, abstractNote={In this paper, we discuss the development of models for PZT bimorph actuators used to power micro-air vehicles including Robobee. Due to the highly dynamic drive regimes required for the actuators, models must quantify the nonlinear, hysteretic, and rate-dependent behavior inherent to PZT. We first employ the homogenized energy model (HEM) framework to model the actuator dynamics. This provides a comprehensive model, which can be inverted and implemented for certain control regimes. We additionally discuss the development of data-driven models and focus on the implementation of a model based on a dynamic mode decomposition (DMD). Finally, we detail attributes of both approaches for uncertainty quantification and real-time control implementation.}, journal={BEHAVIOR AND MECHANICS OF MULTIFUNCTIONAL MATERIALS AND COMPOSITES 2017}, author={Bravo, Nikolas and Smith, Ralph C. and Crews, John}, year={2017} }