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In this paper, the robust global asymptotic stability (RGAS) of generalized static neural networks (SNNs) with linear fractional uncertainties and a constant or time-varying delay is concerned within a novel input–output framework. The activation functions in the model are assumed to satisfy a more general condition than the usually used Lipschitz-type ones. First, by four steps of technical transformations,...
A discontinuous control law is proposed to achieve global asymptotic stabilization for oscillators with bounded delayed input. Only the “position” signal is used to generate the piecewise constant control signal. The asymptotic stability is analyzed by Poincaré Map method and conditions are proposed. The effectiveness of this control law is verified by simulation studies.
This paper proposes a networked sliding mode controller for servomechanical systems. Asymptotic stability is analyzed. Saturation function is used to eliminate chattering. Sensitivity of the zero eigenvalue with respect to the gain of the saturation function in linear interval is analyzed. Conditions for the choice of the gain and time delay are proposed. Simulations are conducted to verify the theoretical...
Oscillators with bounded delayed input are stabilized by a sliding mode control law. In the control law, sign function is replaced by high gain function to avoid chattering in the presence of time delay. A condition is developed to determine the gain. Simulation is conducted to show the effectiveness of the theoretical analysis.
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