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A physics-informed neural networks–based adaptive control for a class of nonlinear systems with nonparametric uncertainties

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Transactions of the Institute of Measurement and Control

Published online on

Abstract

Transactions of the Institute of Measurement and Control, Ahead of Print.
This article addresses the trajectory tracking control problem for a class of nonlinear systems subject to nonparametric uncertainties. Traditional adaptive methods struggle with such uncertainties due to inadequate regression models, while conventional ...