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Nik Bravo, Data-Driven Model Development and Feedback Control Design for PZT Bimorph Actuators and Lider Leon, Parameter and Active Subspace Analysis for a Polydomain Ferroelectric Phase Field Model

September 11, 2017 | 4:00 pm - 5:00 pm EDT

Nik Bravo:
Title: Data-Driven Model Development and Feedback Control Design for PZT Bimorph Actuators

Abstract:
In the talk, 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.
 
Lider Leon:

Title: Parameter and Active Subspace Analysis for a Polydomain Ferroelectric Phase Field Model

Abstract: We consider subset selection and active subspace techniques for parameters in a continuum phase-field polydomain model for ferroelectric materials. This analysis is necessary to mathematically determine the parameter subset or subspace critically affecting the response, prior to model calibration using either experimental or synthetic data constructed using density functional theory (DFT) simulations. For the 180◦ domain wall model, we employ identifiability analysis using a Fisher information matrix methodology, and subspace selection to determine the active subspace. We demonstrate the implementation and interpretation of techniques that accommodate the model structure and discuss results in the context of identifiable parameter subsets and active subspaces quantifying the strongest influence on the model output. 

Details

Date:
September 11, 2017
Time:
4:00 pm - 5:00 pm EDT
Event Category:

Venue

SAS 4201