Semi-active vibration control of structural systems with a neural network that trained preview optimal control for MLD model-Reference-Cited by-同舟云学术

Semi-active vibration control of structural systems with a neural network that trained preview optimal control for MLD model

Published:2021 Issue:901 Volume:87 Page:21-00180-21-00180
ISSN:2187-9761
Container-title:Transactions of the JSME (in Japanese)
language:en
Short-container-title:

Author:

SATO Kaoru¹,HIRAMOTO Kazuhiko²

Affiliation:

1. Graduate School of Niigta University

2. Niigta University

Publisher

Japan Society of Mechanical Engineers

Link

https://www.jstage.jst.go.jp/article/transjsme/87/901/87_21-00180/_pdf

Reference19 articles.

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2. Bemporad, A. and Morari, M., Control of systems integrating logic, dynamics, and constraints, Automatica, Vol.35 (1999), pp.407-427.

3. Bliek, C., Bonami, P. and Lodi, A., Solving mixed-integer quadratic programming problems with IBM-CPLEX: a progress report, Proceedings of the Twenty-Sixth RAMP Symposium (2014).

4. Dyke, S.J., Spencer B. F. and Carlson, J.D., Modeling and control of magnetorheological dampers for seismic response reduction, Smart Materials and Structures, Vol.5, No.5 (1996), pp.565-575.

5. Giorgetti, N., Bemporad, A., Tseng, E. and Hrovat, D., Hybrid model predictive control application towards optimal semi-active suspension, IEEE International Symposium on Industrial Electronics 2005 (2005).

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1. Vibration control of semi-active suspension with MR damper by optimal preview control of MLD model.;Transactions of the JSME (in Japanese);2022