Application of an Off‐Policy Reinforcement Learning Algorithm for H∞${{H}_\infty }$ Control Design of Nonlinear Structural Systems With Completely Unknown Dynamics

ABSTRACT This paper proposes a model‐free and online off‐policy algorithm based on reinforcement learning (RL) for vibration attenuation of earthquake‐excited structures, through designing an optimal H∞${{H}_\infty }$ controller. This design relies on solving a two‐player zero‐sum game theory with a...

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Bibliographic Details
Published in:	Earthquake engineering & structural dynamics Vol. 54; no. 4; pp. 1210 - 1228
Main Authors:	Amirmojahedi, M., Mojoodi, A., Shojaee, Saeed, Hamzehei‐Javaran, Saleh
Format:	Journal Article
Language:	English
Published:	Bognor Regis Wiley Subscription Services, Inc 01.04.2025
Subjects:	Active damping Algorithms Civil engineering Control systems design Controllers Earthquakes Game theory H-infinity control H∞${{H}_\infty }$ control Machine learning Neural networks nonlinear building Nonlinear control Nonlinear systems online reinforcement learning Policies State feedback Strategy System dynamics two‐player zero‐sum game Vibration Zero sum games
ISSN:	0098-8847, 1096-9845
Online Access:	Get full text
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