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An Adaptive Critic Approach to Reference Model AdaptationNeural networks have been successfully used for implementing control architectures for different applications. In this work, we examine a neural network augmented adaptive critic as a Level 2 intelligent controller for a C- 17 aircraft. This intelligent control architecture utilizes an adaptive critic to tune the parameters of a reference model, which is then used to define the angular rate command for a Level 1 intelligent controller. The present architecture is implemented on a high-fidelity non-linear model of a C-17 aircraft. The goal of this research is to improve the performance of the C-17 under degraded conditions such as control failures and battle damage. Pilot ratings using a motion based simulation facility are included in this paper. The benefits of using an adaptive critic are documented using time response comparisons for severe damage situations.
Document ID
20030066166
Acquisition Source
Ames Research Center
Document Type
Preprint (Draft being sent to journal)
Authors
Krishnakumar, K. (NASA Ames Research Center Moffett Field, CA, United States)
Limes, G. (NASA Ames Research Center Moffett Field, CA, United States)
Gundy-Burlet, K. (NASA Ames Research Center Moffett Field, CA, United States)
Bryant, D. (NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
September 7, 2013
Publication Date
May 29, 2003
Subject Category
Aircraft Stability And Control
Meeting Information
Meeting: AIAA GNC Conference
Location: Austin, TX
Country: United States
Start Date: August 11, 2003
End Date: August 14, 2003
Sponsors: American Inst. of Aeronautics and Astronautics
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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