Abstract
An algorithm was proposed to stabilize nonlinear systems with reduced level of impact of the measurement noise, parametric uncertainty, and external perturbation. Consideration was given to the noise of the measurements of dimensionality coinciding with that of the plant state vector. The parametric uncertainty and external perturbations can occur in any equation of the plant model. Conditions were obtained to calculate algorithm parameters in the form of solvability of the linear matrix inequality. Efficiency of the proposed scheme was illustrated by numerical examples.
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