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• W2100021185 abstract "This paper concerns the development, of a robust asymptotic neuro observer (NN) for a class of unknown nonlinear systems with noise disturbances in the output. The suggested asymptotic observer has three basic terms: the first one is introduced to approximate the unknown nonlinear dynamics, the second one is related with the innovation (the standard correction term) and the last one is a time delayed term introduced especially to assure the approximation of the unmeasured state derivatives. The Lyapunov-Krasovskii technique is used to proof the robust asymptotic stability on average of the obtained estimation error. A special dead-zone multiplier is introduced into the learning procedure to guarantee the boundness of the weight matrices of the dynamic NN." @default.
• W2100021185 created "2016-06-24" @default.
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• W2100021185 date "2002-11-08" @default.
• W2100021185 modified "2023-09-25" @default.
• W2100021185 title "Robust asymptotic neuro observer with time delay term" @default.
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• W2100021185 doi "https://doi.org/10.1109/isic.2000.882893" @default.
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