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Adaptive Control as an Information Gradient Flow: Excitation, Constraints, Energy, and Stochastic Learning
Adaptive control is usually developed through Lyapunov stability, excitation, and parameter convergence, whereas neighboring fields describe learning using convexity, information geometry, variational principles, and stochastic thermodynamics. This paper develops a constrained common language for th
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