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Reinforcement learning for vibration suppression of an unknown system

  • Ziemowit DworakowskiEmail author
  • Krzysztof Mendrok
Conference paper
Part of the Mechanisms and Machine Science book series (Mechan. Machine Science, volume 73)

Abstract

The article presents a novel approach to vibration suppression that can be used in cases when system under consideration is unknown. The approach is based on a reinforcement-learning of artificial neural network fed with positions and velocities of the system components. The learning routine is designed on the basis of a 1+1 evolutionary scheme with concept of persistence of efficient steps. The performance of the four variants of the algorithm is evaluated on the basis of a simulated 3-DOF system.

Keywords

Vibration suppression Artificial Neural Network Reinforcement Learning Unknown system Evolutionary approach 

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Notes

Acknowledgement

The work presented in this paper was supported by the National Science Centre in Poland under the research project no. 2016/21/D/ST8/01678.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.AGH University of Science and TechnologyKrakowPoland

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