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Design of Optimal QFT Controller and Prefilter for Buck Converter Using Metaheuristic Algorithms
Author(s) -
Nitish Katal,
Shiv Narayan
Publication year - 2018
Publication title -
modelling and simulation in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 20
eISSN - 1687-5591
pISSN - 1687-5605
DOI - 10.1155/2018/2453817
Subject(s) - control theory (sociology) , robustness (evolution) , parametric statistics , buck converter , voltage , robust control , computer science , controller (irrigation) , control engineering , quantitative feedback theory , engineering , control system , mathematics , control (management) , agronomy , biochemistry , chemistry , statistics , artificial intelligence , biology , electrical engineering , gene
A buck converter is a step-down switching regulator. Buck convertors are being widely used in industrial applications that rely on regulated output voltage under fluctuating input voltage. A buck convertor works in the following modes: (a) current-controlled or (b) voltage-controlled mode. But these convertors manifest several nonlinearites because of the switching operation. Hence, in order to generate a quality output of the convertor, the design of a controller becomes crucial. In this paper, the synthesis of a QFT-based robust controller and prefilter has been carried out for an uncertain buck converter with varying input voltage and varying load. The controller synthesis problem has been posed as an optimization problem, and metaheuristic algorithms have been used for obtaining the optimal gains for the QFT controller and prefilter. By doing this, the QFT synthesis can be carried out in a single step instead of following the sequential classical QFT process on Nichols charts and the need for the generation of templates and bounds has be eliminated. The designed 2-degree-of-freedom QFT control system offers a robust behavior and efficiently handles the parametric uncertainties. The robustness of the designed controller has been confirmed through simulation results for large input voltage and load fluctuations.

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