4.8 Article

Multivariable Optimal Control Applied to a Back-to-Back Power Converter

期刊

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
卷 69, 期 9, 页码 9406-9418

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2021.3114748

关键词

Voltage control; MIMO communication; Tools; Reactive power; Power quality; Microgrids; Frequency control; Back-to-back (BTB) converter; multivariable optimal control; relative gain array (RGA); singular-value decomposition (SVD)

资金

  1. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior-Brasil (CAPES) [001]
  2. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico-Brasil (CNPq)
  3. Instituto Nacional de Energia Eletrica (INERGE)
  4. Fundacao de Amparo a Pesquisa no Estado de Minas Gerais (FAPEMIG)

向作者/读者索取更多资源

This article proposes a scheme for the analysis and control design of a back-to-back (BTB) converter using a multivariable approach. The BTB converter is analyzed as a multiple-input multiple-output system using singular value decomposition and relative gain array, which helps determine the variables that should be controlled within a given frequency range. Based on this analysis, low- and high-frequency controllers are included to track references and reject disturbances. The sensitivity and complementary sensitivity functions are analyzed to fine-tune a centralized optimal linear quadratic multivariable control. Experimental results are presented to validate the effectiveness of the analysis and control design.
This article proposes the analysis and control design of back-to-back (BTB) converter using multivariable approach. Singular value decomposition and relative gain array are used to analyze the BTB converter as a multiple-input multiple-output system and decide which variables should be controlled in a given frequency range. Based on the aforementioned analysis, a suitable low- and high-frequency controllers are included in order to asymptotically track the references and reject disturbances. A systematic approach, analyzing the sensitivity and complementary sensitivity functions, is carried out to tune a centralized optimal linear quadratic multivariable control. Experimental results are presented to validate the analysis and control design.

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