#7127. Vibration Control in Meta-Structures Using Reinforcement Learning

November 2026publication date
Proposal available till 11-05-2025
4 total number of authors per manuscript0 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Aerospace Engineering;
Mechanical Engineering;
Mechanics of Materials;
Places in the authors’ list:
place 1place 2place 3place 4
FreeFreeFreeFree
2350 $1200 $1050 $900 $
Contract №7127.1 Contract №7127.2 Contract №7127.3 Contract №7127.4
1 place - free (for sale)
2 place - free (for sale)
3 place - free (for sale)
4 place - free (for sale)

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.
Keywords:
Bandgap; Q-Learning; Reinforcement learning (RL); Reward function; Stiffness

Contacts :
0