Prescribed-time observer for nonlinear systems is shown to naturally reject bounded disturbances and uncertainties, with proof and simulations demonstrating accurate estimation and superiority over high-gain observers.
Neural network adaptive observer design for nonlinear systems with partially and completely unknown dynamics subject to variable sampled and delay output mea- surement
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Prescribed-Time Observer Is Naturally Robust Against Disturbances and Uncertainties
Prescribed-time observer for nonlinear systems is shown to naturally reject bounded disturbances and uncertainties, with proof and simulations demonstrating accurate estimation and superiority over high-gain observers.