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- W2143934284 abstract "It is difficult to achieve good tracking performance in the presence of modeling error with the use of high adaptation gain. This leads to unnecessary high frequency control effort that can excite unmodeled dynamics. This paper introduces an adaptive control architecture that allows fast adaptation for systems with slow reference models. Fast adaptation is achieved using a high bandwidth state emulator to train a neural network. Low bandwidth control action is maintained using a filter to isolate fast emulator dynamics from the control effort. The usefulness of the architecture is illustrated on a nonlinear model for wing rock and a longitudinal model for a Boeing 747." @default.
- W2143934284 created "2016-06-24" @default.
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- W2143934284 date "2010-04-20" @default.
- W2143934284 modified "2023-09-26" @default.
- W2143934284 title "Adaptive Control for Systems with Slow Reference Models" @default.
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- W2143934284 doi "https://doi.org/10.2514/6.2010-3417" @default.
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