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Journal of Algorithms and Computation
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April 2008
Volume Volume 41 (2007)
Shahi, H., Yousefikoma, A., Mehrabian, A. (2013). شناسایی سیستم و طراحی کنترل بهینه با استفاده از الگوریتم ژنتیک برای کنترل ارتعاشات یک بال هوشمند. Journal of Algorithms and Computation, 42(1), 119-130.
Hossein Shahi; Aghil Yousefikoma; Ali Reza Mehrabian. "شناسایی سیستم و طراحی کنترل بهینه با استفاده از الگوریتم ژنتیک برای کنترل ارتعاشات یک بال هوشمند". Journal of Algorithms and Computation, 42, 1, 2013, 119-130.
Shahi, H., Yousefikoma, A., Mehrabian, A. (2013). 'شناسایی سیستم و طراحی کنترل بهینه با استفاده از الگوریتم ژنتیک برای کنترل ارتعاشات یک بال هوشمند', Journal of Algorithms and Computation, 42(1), pp. 119-130.
Shahi, H., Yousefikoma, A., Mehrabian, A. شناسایی سیستم و طراحی کنترل بهینه با استفاده از الگوریتم ژنتیک برای کنترل ارتعاشات یک بال هوشمند. Journal of Algorithms and Computation, 2013; 42(1): 119-130.

شناسایی سیستم و طراحی کنترل بهینه با استفاده از الگوریتم ژنتیک برای کنترل ارتعاشات یک بال هوشمند

Article 3, Volume 42, Issue 1, April 2008, Page 119-130  XML PDF (1.54 MB)
Document Type: Research Paper
Authors
Hossein Shahi; Aghil Yousefikoma* ; Ali Reza Mehrabian
Abstract
A solution to the problem of identification and control of smart structures is presented in this paper. Smart structures with build-in sensors and actuators can actively and adaptively change their physical geometry and properties. As a particular example, a representative dynamic model of a typical fighter vertical tail, identified as the smart fin, is considered. Piezoelectric patches, which are mounted on the vertical tail, are employed as actuator in the model. The Frequency Response Function (FRF) of the smart fin is obtained from experiment. The corresponding transfer function is then derived using classic system identification (ID) techniques, using MATLAB® system identification toolbox, which is verified with the experimental data. The model obtained using system ID is then used to tune an optimal PID controller to reduce the vibration of the smart structure. To this end, several cost functions are defined and optimized by a genetic algorithm. Next, the obtained controllers are compared with each other and a suitable one is chosen as the system’s controller. Finally, It is shown in simulations that the designed controller is able to reduce the vibration of the smart fin very well.
Keywords
Smart Structures; Dynamic System Identification; Active Vibration Control; Optimized PID Controller; genetic algorithm
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