Modeling of a Motor-driven Propeller Dynamics System by Neural Ordinary Differential Equation

Chao Chung Peng, Yi Ho Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In recent years, the prosperous development of neural network-related technologies has solved lots of problems in the real world, including text generation, image processing and object recognition. Fewer studies are used for system dynamics modeling, simulation, and identification. To simulate the transient response of a dynamical system, most of the studies applied recurrent neural network (RNN), which uses feedback connections to consider the influence of past state when computing current state. However, it still needs a much larger structure relative to the order of the system dynamics for neural network to have a good fitting performance. To reduce the model complexity and increase the accuracy, this paper presents a data-driven based modeling for a motor-driven propeller system by applying the neural ordinary differential equation (i.e., neural ODE). It is worthy to note that the neural ODE builds a continuous-time model for system identification, which can reduce large amount of memory demands to store the past states generated by the RNN. By comparing with the exact physical model, the discrete-time RNN, and the nonlinear autoregressive with exogenous (NARX) model, numerical simulations show that the proposed neural ODE model gives the best fitting results in the presence of measurement noise.

Original languageEnglish
Title of host publicationProceedings - 2023 6th International Symposium on Computer, Consumer and Control, IS3C 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages284-287
Number of pages4
ISBN (Electronic)9798350301953
DOIs
Publication statusPublished - 2023
Event6th International Symposium on Computer, Consumer and Control, IS3C 2023 - Taichung City, Taiwan
Duration: 2023 Jun 302023 Jul 3

Publication series

NameProceedings - 2023 6th International Symposium on Computer, Consumer and Control, IS3C 2023

Conference

Conference6th International Symposium on Computer, Consumer and Control, IS3C 2023
Country/TerritoryTaiwan
CityTaichung City
Period23-06-3023-07-03

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Human-Computer Interaction
  • Control and Optimization

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