Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network
Joint Authors
Hiramoto, Kazuhiko
Matsuoka, Taichi
Sunakoda, Katsuaki
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-01-15
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
We propose an adaptive gain scheduled semiactive control method using an artificial neural network for structural systems subject to earthquake disturbance.
In order to design a semiactive control system with high control performance against earthquakes with different time and/or frequency properties, multiple semiactive control laws with high performance for each of multiple earthquake disturbances are scheduled with an adaptive manner.
Each semiactive control law to be scheduled is designed based on the output emulation approach that has been proposed by the authors.
As the adaptive gain scheduling mechanism, we introduce an artificial neural network (ANN).
Input signals of the ANN are the measured earthquake disturbance itself, for example, the acceleration, velocity, and displacement.
The output of the ANN is the parameter for the scheduling of multiple semiactive control laws each of which has been optimized for a single disturbance.
Parameters such as weight and bias in the ANN are optimized by the genetic algorithm (GA).
The proposed design method is applied to semiactive control design of a base-isolated building with a semiactive damper.
With simulation study, the proposed adaptive gain scheduling method realizes control performance exceeding single semiactive control optimizing the average of the control performance subject to various earthquake disturbances.
American Psychological Association (APA)
Hiramoto, Kazuhiko& Matsuoka, Taichi& Sunakoda, Katsuaki. 2018. Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network. Shock and Vibration،Vol. 2018, no. 2018, pp.1-19.
https://search.emarefa.net/detail/BIM-1215206
Modern Language Association (MLA)
Hiramoto, Kazuhiko…[et al.]. Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network. Shock and Vibration No. 2018 (2018), pp.1-19.
https://search.emarefa.net/detail/BIM-1215206
American Medical Association (AMA)
Hiramoto, Kazuhiko& Matsuoka, Taichi& Sunakoda, Katsuaki. Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network. Shock and Vibration. 2018. Vol. 2018, no. 2018, pp.1-19.
https://search.emarefa.net/detail/BIM-1215206
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1215206