Experimental Identification of a Self-Sensing Magnetorheological Damper Using Soft Computing-Reference-Cited by-同舟云学术

Experimental Identification of a Self-Sensing Magnetorheological Damper Using Soft Computing

Published:2015-07 Issue:7 Volume:141 Page:04015001
ISSN:0733-9399
Container-title:Journal of Engineering Mechanics
language:en
Short-container-title:J. Eng. Mech.

Author:

Ni Y. Q.¹,Chen Z. H.²,Or S. W.³

Affiliation:

1. Professor, Dept. of Civil and Environmental Engineering, Hong Kong Polytechnic Univ., Hung Hom, Kowloon, Hong Kong (corresponding author).

2. Assistant Professor, College of Civil Engineering, Fuzhou Univ., 350116 Fujian, China; formerly, Ph.D. Student, Dept. of Civil and Environmental Engineering, Hong Kong Polytechnic Univ., Hung Hom, Kowloon, Hong Kong.

3. Professor, Dept. of Electrical Engineering, Hong Kong Polytechnic Univ., Hung Hom, Kowloon, Hong Kong.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Mechanics of Materials

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29EM.1943-7889.0000930

Reference45 articles.

1. Modeling of a magnetorheological damper by recursive lazy learning

2. Scalable and Invertible PMNN Model for MagnetoRheological Fluid Dampers

3. MR fluid, foam and elastomer devices

4. Neural Network Modeling of a Magnetorheological Damper

5. Neural Network Emulation of Inverse Dynamics for a Magnetorheological Damper

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