Multi-objective optimization for vibration suppression of smart laminated composites
The present paper proposes a multi-objective optimization technique for smart laminated composites to maximize two conflicting objectives. The first objective is the performance of active vibration control of smart composite with piezoelectric (PZT) actuators. The second is the fundamental frequency...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
The Japan Society of Mechanical Engineers
2016
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/e41062feae244de8b886f862e137db8f |
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| Sumario: | The present paper proposes a multi-objective optimization technique for smart laminated composites to maximize two conflicting objectives. The first objective is the performance of active vibration control of smart composite with piezoelectric (PZT) actuators. The second is the fundamental frequency of smart structures related to the performance of passive vibration control. Both performances of active and passive vibration control are maximized simultaneously. The vibration suppression of smart structures strongly depends on both actuator placements and vibration mode shapes. It is possible to design vibration mode shapes for laminated fibrous composites since their anisotropy for whole thickness is tailorable by arranging fiber orientation angle in each layer. This allows the smart structure with laminated composite to archive higher performance of vibration suppression than those with isotropic materials. However, the optimized structure results in lower natural frequencies than composites with typical fiber orientation angles since an effective input of control force from actuators is realized for the structure with lower stiffness. This reveals that there is a trade-off relation for smart composite structures between the performance of active vibration suppression and natural frequencies. To disclose this relation, the present study applies the effective multi-objective optimization technique, the refined non-dominated genetic algorithm (NSGAII), and obtains Pareto optimal solutions. Calculated results are successfully validated by a comparison with those from the real-time control experiment where a laser excitation technique which is effective to small sized structures is used. |
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