Tese: Nonlinear Black-box Identification of Piezoelectric Systems
Aluno(a) : Matheus Patrick Soares BarbosaOrientador(a): Helon Ayala
Área de Concentração: Mecânica Aplicada
Data: 26/04/2021
Link para tese/dissertação: https://doi.org/10.17771/PUCRio.acad.54640
Resumo: Actuators based on piezoelectric materials are portable, manage small displacements while maintaining high resolution, frequency and stiffness. Those properties make them ideal for application such as acoustic transmission and micromanipulation. But inherent nonlinearities to those actuators, such as hysteresis and creep, greatly increases the challenge to control such devices. Furthermore, the increasing need for more precise and faster actuators, allied with frequent changes in the environmental conditions and complex dynamics related to the mechanical displacement induced by the excitation signal fur-ther worsens the problem. Analytical models are application-specific, mean-ing that they are not easily and efficiently scalable to all systems. Also, with increased complexity, the understating of underlying phenomena is not fully documented, making it difficult to develop such models. This work investigates those challenges from the perspective of the system identification methodology and data-driven models for piezoelectric actuators. Those are powerful tools that vary considerably according to the modeling criteria and the black-box approach is tested with experimental data acquired in a laboratory setting for a micromanipulator and acoustic transmission test benches. The results show good capabilities to compensate the nonlinearities for the micromanipulator, by predicting the hysteresis at different input frequencies. The acoustic trans-mission system was successfully modeled and although the results show that are still room for improvements, it provides insights in possible optimizations for the setup as the models here devised are useful for short prediction win-dows. Furthermore, this encourages further research in the pursuit of better data-driven abstractions for the piezoacoustic transmission and micromanipu-lation applications.