2020
DOI: 10.1109/tii.2019.2910841
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Disturbance Rejection for Nonlinear Uncertain Systems With Output Measurement Errors: Application to a Helicopter Model

Abstract: As a virtual sensor, disturbance observer provides an alternative approach to reconstruct lumped disturbances (including external disturbances and system uncertainties) based upon system states/outputs measured by physical sensors. Not surprisingly, measurement errors bring adverse effects on the control performance and even the stability of the closed-loop system. Toward this end, this paper investigates the problem of disturbance observer based control for a class of disturbed uncertain nonlinear systems in … Show more

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Cited by 26 publications
(7 citation statements)
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“…The prediction model for the speed of PMSG can be obtained by subtracting the two equations in equation (13), since it can be written as follows…”
Section: Composite Mpc Based On the Speed Sensorless Methodsmentioning
confidence: 99%
“…The prediction model for the speed of PMSG can be obtained by subtracting the two equations in equation (13), since it can be written as follows…”
Section: Composite Mpc Based On the Speed Sensorless Methodsmentioning
confidence: 99%
“…The second category focuses on utilising the disturbance observer to improve the robustness and disturbance rejection performance of MPC methods. Disturbance observer is a kind of special soft sensor to estimate the lumped effect of system uncertainties and external disturbances (see [17][18][19][20], and the references therein). These approaches can also be sketchily classified into the following two branches:…”
Section: Introductionmentioning
confidence: 99%
“…In many industrial applications, such as robotics systems [1]- [3], servo-control systems [4], [5], and power commutators [6], the performance of control systems mainly suffers from uncertainties like parameter uncertainties, external disturbances, and unmodeled dynamics. To cope with this issue, a number of approaches have been explored, where the concept of uncertainty estimation, disturbance compensation, and observer-based control strategies, have been increasingly studied and employed successfully in a wide range of this fields [7]- [9], [10], [11]. These control algorithms aim to estimate the uncertainties and disturbances that exerts on uncertain nonlinear systems (UNS).…”
Section: Introductionmentioning
confidence: 99%