Air Spring Controlled by Reinforcement Learning Algorithm

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24210%2F20%3A00008299" target="_blank" >RIV/46747885:24210/20:00008299 - isvavai.cz</a>
Result on the web
<a href="https://www.engmech.cz/im/im/page/proc" target="_blank" >https://www.engmech.cz/im/im/page/proc</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.21495/5896-3-428" target="_blank" >10.21495/5896-3-428</a>

Result language
angličtina
Original language name
Air Spring Controlled by Reinforcement Learning Algorithm
Original language description
The paper deals with the replacement of the analog PID stroke controller of a bellows pneumatic spring, by machine learning algorithms, specifically deep reinforcement learning. The Deep Deterministic Policy Gradient (DDPG) algorithm used consists of an environment, in this case a pneumatic spring, and an agent which, based on observations of environment, performs actions that lead to the cumulative reward it seeks to maximize. DDPG falls into the category of actor-critic algorithms. It combines the benefits of Q-learning and optimization of a deterministic strategy. Q-learning is represented here in the form of critic, while optimization of strategy is represented in the form of an actor that directly maps the state of the environment to actions. Both the critic and the actor are represented in deep reinforcement learning by deep neural networks. Both of these networks have a target variant of themselves. These target networks are designed to increase the stability and speed of the learning process. The DDPG algorithm also uses a replay buffer, from which the data from which the agent learns is taken in batches.
Czech name
—
Czech description
—

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Engineering Mechanics 2020
ISBN
978-80-214-5896-3
ISSN
1805-8248
e-ISSN
—
Number of pages
4
Pages from-to
428-431
Publisher name
Brno University of Technology Institute of Solid Mechanics, Mechatronics and Biomechanics
Place of publication
Brno
Event location
Brno
Event date
Jan 1, 2020
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000667956100099

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