Paper
22 June 2000 Neural net-based controller for flutter suppression using ASTROS with smart structures
Changho Nam, P. C. Chen, Danny D. Liu, Aditi Chattopadhyay, Jongsun Kim
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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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Changho Nam, P. C. Chen, Danny D. Liu, Aditi Chattopadhyay, and Jongsun Kim "Neural net-based controller for flutter suppression using ASTROS with smart structures", Proc. SPIE 3985, Smart Structures and Materials 2000: Smart Structures and Integrated Systems, (22 June 2000); https://doi.org/10.1117/12.388808
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Cited by 7 scholarly publications.
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KEYWORDS
Neural networks

Ferroelectric materials

Actuators

Smart structures

Aerodynamics

Control systems

Control systems design

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