Neural net based controller for flutter suppression using ASTROS with smart structures

Changho Nam, P. C. Chen, D. D. Liu, Aditi Chattopadhyay, J. Kim

Research output: Chapter in Book/Report/Conference proceedingChapter

7 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSociety of Photo-Optical Instrumentation Engineers
Pages98-109
Number of pages12
Volume3985
StatePublished - 2000
Externally publishedYes
EventSmart Structures and Materials 2000 - Smart Structures and Integrated Systems - Newport Beach, CA, USA
Duration: Mar 6 2000Mar 9 2000

Other

OtherSmart Structures and Materials 2000 - Smart Structures and Integrated Systems
CityNewport Beach, CA, USA
Period3/6/003/9/00

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

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