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Application of artificial bee colony algorithm to auto-tuning of state feedback controller for DC-DC power converter

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EN
Abstrakty
EN
The article presents an auto-tuning method of state feedback voltage controller for DC-DC power converter. The penalty matrices employed for calculation of controller’s coefficients were obtained by using nature-inspired artificial bee colony (ABC) optimization algorithm. This overcomes the main drawback of state feedback control related to time-consuming trial-and-error tuning procedure. The optimization algorithm takes into account constraints of selected state and control variables of DC-DC power converter. In order to meet all control objectives (i.e., fast voltage response and chattering-free control signal) an appropriate performance index is proposed. Proper selection of state feedback controller (SFC) coefficients is proven by simulation and experimental tests of DC-DC power converter.
Wydawca
Rocznik
Strony
83--96
Opis fizyczny
Bibliogr. 18 poz., rys., tab.
Twórcy
  • Nicolaus Copernicus University in Toruń, Institute of Physics, Faculty of Physics, Astronomy and Informatics, ul. Grudziądzka 5, 87-100 Toruń, Poland
  • Nicolaus Copernicus University in Toruń, Institute of Physics, Faculty of Physics, Astronomy and Informatics, ul. Grudziądzka 5, 87-100 Toruń, Poland
  • Warsaw University of Technology, Institute of Control and Industrial Electronics, ul. Koszykowa 75, 00-662 Warszawa, Poland
Bibliografia
  • [1] LINARES-FLORES J., SIRA-RAMIREZ H., DC motor velocity control through a DC-to-DC power converter, Proc. of IEEE Decision and Control Conf. CDC, 2004, 5, 5297–5302.
  • [2] TARCZEWSKI T., NIEWIARA Ł., GRZESIAK L.M., Torque ripple minimization for PMSM using voltage matching circuit and neural network based adaptive state feedback control, Proc. of IEEE EPE 14-ECCE Conf., 2014, 1–10.
  • [3] FANG J., LI W., Li H., XU X., Online inverter fault diagnosis of Buck-Converter BLDC motor combinations, IEEE Trans. Power Electronics, 2015, 30, 5, 2674–2688.
  • [4] FENG G., MEYER E., LIU Y.F., A new digital control algorithm to achieve optimal dynamic performance in DC-to-DC converters, IEEE Trans. Power Electronics, 2007, 22, 4, 1489–1498.
  • [5] LING R., MAKSIMOVIC D., LEYVA R., Second-order sliding-mode controlled synchronous buck DCDC converter, IEEE Trans. Power Electronics, 2016, 31, 3, 2539–2549.
  • [6] TARCZEWSKI T., GRZESIAK L., Constrained state feedback speed control of PMSM based on model predictive approach, IEEE Trans. Industrial Electronics, 2016, 63, 6, 3867–3875.
  • [7] TARCZEWSKI T., NIEWIARA Ł., GRZESIAK L.M., Constrained state feedback control of DC-DC power converter based on model predictive approach, Proc. of IEEE EFEA Conf., 2016, 1–6.
  • [8] SAFONOV M.G., ATHANS M., Gain and phase margin for multiloop LQG regulators, IEEE Trans. Automatic Control, 1977, 22, 2, 173–179.
  • [9] ROBANDI I., NISHIMORI K., NISHIMURA R., ISHIHARA N., Optimal feedback control design using genetic algorithm in multimachine power system, International Journal of Electrical Power and Energy Systems, 2001, 23, 4, 263–271.
  • [10] UFNALSKI B., GRZESIAK L.M., Particle swarm optimization of artificial neural-network-based online trained speed controller for battery electric vehicle, Bulletin of the Polish Academy of Sciences: Technical Sciences, 2012, 60, 3, 661–667.
  • [11] KAMIŃSKI M., Design of adaptive state space controller for two-mass system using BAT algorithm, Proc. of SENE Conf. 2015, (in Polish).
  • [12] KARABOGA D., BASTURK B., A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm, Journal of Global Optimization, 2007, 39, 3, 459–471.
  • [13] KARABOGA D., BASTURK B., On the performance of artificial bee colony (ABC) algorithm, Applied Soft Computing, 2008, 8, 1, 687–697.
  • [14] SIRA-RAMIREZ H., SILVA-ORTIGOZA R., Control Design Techniques in Power Electronics Devices, Springer-Verlag, London, 2006.
  • [15] GRZESIAK L.M., TARCZEWSKI T., PMSM servo-drive control system with a state feedback and a load torque feedforward compensation, COMPEL, 2013, 32, 1, 364–382.
  • [16] KARABOGA D., AKAY B., A modified artificial bee colony (ABC) algorithm for constrained optimization problems, Applied Soft Computing, 2011, 11, 3, 3021–3031.
  • [17] GOLDBERG D.E., DEB K., A comparison of selection schemes used in genetic algorithms, Foundations of Genetic Algorithms, 1991, 69–93.
  • [18] KARABOGA D., BASTURK, B., Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems, International Fuzzy Systems Association World Congress, 2007, 789–798.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-cd8b8366-2da9-430d-b465-a4301c1826f7
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