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Proceedings Paper

Neural net-based controller for flutter suppression using ASTROS with smart structures
Author(s): Changho Nam; P. C. Chen; Danny D. Liu; Aditi Chattopadhyay; Jongsun Kim
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Paper Abstract

Recent development of a smart structures module and its successful integration with a multidisciplinary design optimization software ASTROS* and an Aeroservoelasticity (ASE) module is presented. A modeled F-16 wing using piezoelectric (PZT) actuators was used as an example to demonstrate the integrated software capability to design a flutter suppression system. For an active control design, neural network based robust controller will be used for this study. A smart structures module is developed by modifying the existing thermal loads module in ASTROS* in order to include the effects of the induced strain due to piezoelectric (PZT) actuation. The thermal-PZT equivalence model enables the modifications of the thermal stress module to accommodate the smart structures module in ASTROS*. ZONA developed the control surface (CS)/PZT equivalence model principle, which ensures the interchangeability between the CS force input and the PZT force input to the ASE modules in ASTROS*. The results show that the neural net based controller can increase the flutter speed.

Paper Details

Date Published: 22 June 2000
PDF: 12 pages
Proc. SPIE 3985, Smart Structures and Materials 2000: Smart Structures and Integrated Systems, (22 June 2000); doi: 10.1117/12.388808
Show Author Affiliations
Changho Nam, ZONA Technology Inc. (United States)
P. C. Chen, ZONA Technology Inc. (United States)
Danny D. Liu, Arizona State Univ. (United States)
Aditi Chattopadhyay, Arizona State Univ. (United States)
Jongsun Kim, Arizona State Univ. (United States)


Published in SPIE Proceedings Vol. 3985:
Smart Structures and Materials 2000: Smart Structures and Integrated Systems
Norman M. Wereley, Editor(s)

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