Jorge Cortés
Professor
Cymer Corporation Endowed Chair
Controller design for bilinear neural feedback loops
D. Shah, J. Cortés
IEEE Control Systems Letters, submitted
Abstract
This paper considers a class of bilinear systems with
a neural network in the loop. These arise naturally when employing
machine learning techniques to approximate general, non-affine in
the input, control systems. We propose a controller design
framework that combines linear fractional representations and tools
from linear parameter varying control to guarantee local exponential
stability of a desired equilibrium. The controller is obtained from
the solution of linear matrix inequalities, which can be solved
offline, making the approach suitable for online applications. The
proposed methodology offers tools for stability and robustness
analysis of deep neural networks interconnected with dynamical
systems.
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Mechanical and Aerospace Engineering,
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