publications

2020

1. IFAC

   Evaluation of Nonlinear System Identification to Model Piezoacoustic Transmission

   Matheus Patrick Soares Barbosa, Daniel Pereira da Costa, and Helon Vicente Hultmann Ayala

   IFAC-PapersOnLine, 2020

   21st IFAC World Congress

   Abs Bib HTML

   Piezoeletric materials are used on high-precision and high-dynamics applications, such as for acoustic transmission. This paper covers the challenges of creating a black-box model for a simultaneous acoustic transmission problem, with data acquired in a laboratory setup. The system performance is analyzed for three different models: AutoRegressive Moving Average with eXogenous inputs (ARMAX) model, Nonlinear AutoRegressive with eXogenous inputs (NARX) model with artificial neural network structure, and Nonlinear AutoRegressive Moving Average with eXogenous inputs (NARMAX) models. The best results of each models are compared with respect to precision in free-run simulation. The prediction results show that the most complex NARMAX model had the best results, what encourages further research in creating nonlinear mathematical data-driven abstractions for the piezoacoustic transmission application.

   @article{SOARESBARBOSA20208802,
     title = {Evaluation of Nonlinear System Identification to Model Piezoacoustic Transmission},
     journal = {IFAC-PapersOnLine},
     volume = {53},
     number = {2},
     pages = {8802-8807},
     year = {2020},
     note = {21st IFAC World Congress},
     issn = {2405-8963},
     doi = {https://doi.org/10.1016/j.ifacol.2020.12.1386},
     url = {https://www.sciencedirect.com/science/article/pii/S2405896320317961},
     author = {{Soares Barbosa}, Matheus Patrick and {da Costa}, Daniel Pereira and {Hultmann Ayala}, Helon Vicente},
     keywords = {Identification, control methods, Smart Structures, Mechatronics, Nonlinear system identification, Artificial Neural Networks, Piezoacoustic Transmission},
   }

2019

1. PUC

   Comparison of linear and nonlinear methods for systems identification with piezoeletric materials and acoustic transmission

   Daniel Pereira da Costa

   Maxwell PUC-Rio, 2019

   Abs HTML

   Piezoelectric materials are materials capable of producing an electric current when subjected to mechanical stress. On the other hand, these materials are physically deformed when an electric field is applied to them. In this work, piezoelectrics are used for data acquisition through an acoustic tunnel and thus apply systems identification techniques to the system modeling process. This work aims to identify an acoustic transmission system through black box system identification methods. Specifically, the AutoRegressive with eXogenous Inputs (ARX) and AutoRegressive Moving Average with eXogenous Inputs (ARMAX) linear models and Nonlinear AutoRegressive with eXogenous Inputs (NARX) model with artificial neural network structure are used. This project encompasses all stages of a systems identification process, from data acquisition to results. The results obtained are compared with the ARX model and the ARMAX model. The prediction conclusion shows that the best result was obtained with the ARMAX model.