Vibration Control in Meta-Structures Using Reinforcement Learning
Document Type
Conference Proceeding
Publication Date
1-1-2022
Department
Department of Mechanical Engineering-Engineering Mechanics
Abstract
This chapter considers using reinforcement learning (RL) to adaptively tune frequency response functions of meta-structures. RL algorithm tunes the stiffness of the spring of the lumped multi-DOF system, as the lumped mass is varied. As some of the lumped masses are modified by 10%, the spring’s stiffness is tuned to maintain the original bandgap. A Q-Learning algorithm is used for RL, wherein the Q-value is updated based on Bellman’s equation. The results compare the frequency response functions of the terminal masses of the baseline and varied mass structure.
Publication Title
Conference Proceedings of the Society for Experimental Mechanics Series
ISBN
9783030759131
Recommended Citation
Mehta, D.,
&
Malladi, V.
(2022).
Vibration Control in Meta-Structures Using Reinforcement Learning.
Conference Proceedings of the Society for Experimental Mechanics Series, 55-58.
http://doi.org/10.1007/978-3-030-75914-8_6
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/15464