An immune optimization deep reinforcement learning control method used for magnetorheological elastomer vibration absorber-Reference-Cited by-同舟云学术

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An immune optimization deep reinforcement learning control method used for magnetorheological elastomer vibration absorber

Published:2024-11 Issue: Volume:137 Page:109108
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Wang Chi,Cheng Weiheng^ORCID,Zhang Hongli,Dou Wei,Chen Jinbo

Funder

National Aerospace Science Foundation of China

Shanghai Aerospace Science and Technology Innovation Foundation

Key Research and Development Program of Zhejiang Province

Shanghai Engineering Research Center of Pressure Pipeline Intelligent Inspection

Publisher

Elsevier BV

Reference39 articles.

1. Deep deterministic policy gradient virtual coupling control for the coordination and manoeuvring of heterogeneous uncertain nonlinear high-speed trains;Basile;Eng. Appl. Artif. Intell.,2024

2. Semi-active suspension control using “fast” model-predictive techniques;Canale;IEEE Trans. Control Syst. Technol.,2006

3. Semi-active variable stiffness vibration control of vehicle seat suspension using an MR elastomer isolator;Du;Smart Mater. Struct.,2011

4. A low frequency horizontal vibration reduction method for a vehicle-borne photoelectric instrument;Du;Vibration and Shock,2017

5. PID Control for magnetorheological elastomer absorber with impact load;Fu;Appl. Mech. Mater.,2012

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