Project/Area Number |
11650257
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Dynamics/Control
|
Research Institution | SETSUNAN UNIVERSITY |
Principal Investigator |
TAKAWA Takeshi SETSUNAN UNIVERSITY, DEPARTMENT OF INDUSTRIAL AND SYSTEMS ENGINEERING, PROFESSOR, 工学部, 教授 (60236370)
|
Co-Investigator(Kenkyū-buntansha) |
FUKUDA Takehito OSAKA CITY UNIVERSITY, DEPARTMENT OF INTELLIGENT MATERIALS ENGINEERING, PROFESSOR, 工学部, 教授 (40047155)
|
Project Period (FY) |
1999 – 2000
|
Project Status |
Completed (Fiscal Year 2000)
|
Budget Amount *help |
¥2,400,000 (Direct Cost: ¥2,400,000)
Fiscal Year 2000: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1999: ¥1,900,000 (Direct Cost: ¥1,900,000)
|
Keywords | Smart CFRP Composites / Piezoceramics / ERF / Vibration Control / Fuzzy Model / LMI / Neural Network / Nonlinearity / 複合材構造物 / アクチュエータ / インテリジェント制御 |
Research Abstract |
The application of intelligent control method to vibration control of a composite CFRP beam was investigated. The results obtained are summarized as follows ; (1) A carbon fiber reinforced plastics (CFRP) beam including interleaved electro-rheological fluids (ERF) and bonded piezoceramics was prepared and oscillated under the forced sinusoidal external excitations. Fuzzy model of controlled element containing two actuators was formed because of intensive nonlinearity in ERF actuator. Parameters of fuzzy model were identified by using a hybrid neuro-fuzzy system. (2) Fuzzy controller for vibration suppression of the composite beam was designed based on the fuzzy model by using the optimum regulator method and the idea of parallel dispersive compensation. The stability of the control system was analyzed with trial and error. The effect of vibration control system satisfying the stability conditions was verified by simulation and experiments. (3) Linear matrix inequalities (LMI) satisfying the stability conditions were derived by the use of Lyapunov's stability theory. The stability analysis of the control system became practicable easily without trial and error by solving the LMI.
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