2020
DOI: 10.1080/00207721.2020.1836283
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H2/H formulation of LQR controls based on LMI for continuous-time uncertain systems

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Cited by 11 publications
(2 citation statements)
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“…Since power conversion systems should be operated with high efficiency as well as improved flexibility and profitability, many authors have a tendency to focus on robust algorithm, adaptive algorithm or learning algorithm to obtain the stabilization of the entire system even in the presence of harsh conditions of the utility grid [6,[11][12][13][14][15][16]. The linear quadratic regulators (LQR) were proposed as a method to determine the optimal controller gains by means of a cost function minimization [17,18].…”
Section: Introductionmentioning
confidence: 99%
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“…Since power conversion systems should be operated with high efficiency as well as improved flexibility and profitability, many authors have a tendency to focus on robust algorithm, adaptive algorithm or learning algorithm to obtain the stabilization of the entire system even in the presence of harsh conditions of the utility grid [6,[11][12][13][14][15][16]. The linear quadratic regulators (LQR) were proposed as a method to determine the optimal controller gains by means of a cost function minimization [17,18].…”
Section: Introductionmentioning
confidence: 99%
“…Even though these studies provide satisfactory performance under parametric uncertainties, several external disturbances such as grid voltage imbalance degrade the current controller operations. Another approach [12] employs H∞ control to cope with the additional grid impedance caused by the weak grid. The robust performance of H∞ control is guaranteed even under parametric uncertainties.…”
Section: Introductionmentioning
confidence: 99%