| Project/Area Number |
08455214
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
構造工学・地震工学
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| Research Institution | Kansai University |
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Principal Investigator |
FURUTA Hitoshi Kansai University, Faculty of Informatics, Professor, 総合情報学部, 教授 (70109031)
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| Co-Investigator(Kenkyū-buntansha) |
KOBAYASHI Takashi Kansai University, Faculty of Informatics, Lecturer, 総合情報学部, 専任講師 (90268334)
TANAKA Shigenori Kansai University, Faculty of Informatics, Associate Professor, 総合情報学部, 助教授 (50268330)
HIROKANE Michiyuki Kansai University, Faculty of Informatics, Associate Professor, 総合情報学部, 助教授 (70268332)
EZAWA Yoshinori Kansai University, Faculty of Informatics, Professor, 総合情報学部, 教授 (90098103)
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| Project Period (FY) |
1996 – 1997
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| Project Status |
Completed (Fiscal Year 1997)
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| Budget Amount *help |
¥2,400,000 (Direct Cost: ¥2,400,000)
Fiscal Year 1997: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 1996: ¥1,500,000 (Direct Cost: ¥1,500,000)
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| Keywords | Chaos Theory / Wind Velocity / Short-Term Prediction / Active Control / Genetic Algorithm / Fuzzy Control / テセレーション法 |
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| Research Abstract |
The main content of the present study is the development of a new method of active control. Active control features very short processing times consumed in evaluating the inputs of detected data and calculating the controlling force, quite simple programming of calculation, wide applicability, good adaptability to the irregular vibration by wind and seismic loads, and so on. Besides, the uncertainty in the natural vibration characteristics of actual structures can be dealt with by using fuzzy control. In general, in the optimal control theory, the controlling force theoretically determined in accordance with the condition of a structure at every moment is applied to it to achieve the optimal control effect. With some actuators, however, it is difficult to regulate such controlling force to the exact value theoretically correct. The fuzzy control allows up to pertform an efficient control even with controlling force in an vague form.
In the present study, wind loads on a structure were taken up as its external force, and the accuracy of the fuzzy active control was improved by making the short-term prediction of wind velocity. In concrete terms, the wind velocity was considered time-series data in chaotic behavior, and the velocity in the next time period was predicted based on the time-series data by using the local fuzzy reconstruction method. The controlling force was determined based on the predicted wind velocity by applying fuzzy control rules. Upon the advent of the actual wind velocity, the controlling force was applied to the structure to curb its amplitude and acceleration. By solving the vibration equation by the Runge-Kutta method, numerical simulation was performed to verify the effectivity of this method.
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