| Issue |
MATEC Web of Conferences
Volume 362, 2022
XXII International Conference on Computational Mechanics and Modern Applied Software Systems (CMMASS 2021)
|
|
|---|---|---|
| Article Number | 01010 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/matecconf/202236201010 | |
| Published online | 14 September 2022 | |
Application of spike neural network for stabilizing pendulum in the nonlinear formulation
1 Kazan Federal University, 18, Kremlyovskaya st., Kazan, 420008, Russia
2 Goethe-Universität Frankfurt am Main, 6 (PEG Building), Theodor-W.-Adorno-Platz, Frankfurt am Main, 60323, Germany
* e-mail: ivanovaanastasya0449@gmail.com
The article describes the solution to the problem of stabilizing a nonlinear system using machine learning methods. Neural networks are one of the promising directions in this area. The article describes a model of spiking neural network, which differs from previous generations of networks by its similarity to biological neurons. A pendulum on an elastic foundation was chosen as a dynamic system for the study. The input layer of the neural network is the so-called sensory neuron, and information about the deviation of the pendulum from the equilibrium position was received on it. The Leaky Integrate-and-Fire model of the spiking neural network was used. The article shows the process of stabilization of a pendulum on an elastic foundation. The closed system was built and a method for a numerical solution was implemented. Two configurations of control functions have been considered. It is shown that the time required to bring the system into a steady equilibrium state depends on the choice of the control function.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.