nach oben

Erschienen in:

2021 | OriginalPaper | Buchkapitel

BELBIC Based Step-Down Controller Design Using PSO

verfasst von : João Paulo Coelho, Manuel Braz-César, José Gonçalves

Erschienen in: Optimization, Learning Algorithms and Applications

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

This article presents a comparison between a common type III controller and one based on a brain emotional learning paradigm (BELBIC) parameterized using a particle swarm optimization algorithm (PSO). Both strategies were evaluated regarding the set-point accuracy, disturbances rejection ability and control effort of a DC-DC buck converter. The simulation results suggests that, when compared to the common controller, the BELBIC leads to an increase in both set-point tracking and disturbances rejection ability while reducing the dynamics of the control signal.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel ERP Business Speed – A Measuring Framework

Nächstes Kapitel Robotic Welding Optimization Using A* Parallel Path Planning

Sankarganesh, R., Thangavel, S.: Performance analysis of various DC-DC converters with optimum controllers for PV applications. Res. J. Appl. Sci. Eng. Technol. 8, 929–941 (2014)CrossRef

Khorashadizadeh, S., Mahdian, M.: Voltage tracking control of DC-DC boost converter using brain emotional learning. In: 4th International Conference on Control, Instrumentation, and Automation (ICCIA), pp. 268–272 (2016)

Erickson, R.W., Maksimovic, D.: Fundamentals of Power Electronics, 2nd edn. Springer, Boston (2001). https://doi.org/10.1007/b100747CrossRef

Sarpeshkar, R.: Neuromorphic and Biomorphic Engineering Systems. McGraw-Hill Yearbook of Science and Technology. McGraw-Hill, New York (2009)

Balkenius, C., Morén, J.: A computational model of emotional learning in the amygdala. Cybern. Syst. 32(6), 611–636 (2001)CrossRef

Lucas, C., Shahmirzadi, D., Sheikholeslami, N.: Introducing BELBIC: brain emotional learning based intelligent controller. Intell. Autom. Soft Comput. 10, 11–22 (2004)CrossRef

Rouhani, H., Jalili, M., Araabi, B.N., Eppler, W., Lucas, C.: Brain emotional learning based intelligent controller applied to neurofuzzy model of micro-heat exchanger. Expert Syst. Appl. 32(3), 911–918 (2007)CrossRef

Rahman, M.A., Milasi, R.M., Lucas, C., Araabi, B.N., Radwan, T.S.: Implementation of emotional controller for interior permanent-magnet synchronous motor drive. IEEE Trans. Ind. Appl. 44(5), 1466–1476 (2008)CrossRef

Nahian, S.A., Truong, D.Q., Ahn, K.K.: A self-tuning brain emotional learning based intelligent controller for trajectory tracking of electrohydraulic actuator. J. Syst. Control Eng. 228, 461–475 (2014)

10.

Coelho, J.P., Pinho, T.M., Boaventura-Cunha, J., de Oliveira, J.B.: A new brain emotional learning Simulink \(\textregistered \) toolbox for control systems design. IFAC-PapersOnLine 50, 16009–16014 (2017)CrossRef

11.

Jafarzadeh, S., Jahed Motlagh, M.R., Barkhordari, M., Mirheidari, R.: A new Lyapunov based algorithm for tuning BELBIC controllers for a group of linear systems. In: 2008 16th Mediterranean Conference on Control and Automation. IEEE, June 2008

12.

Garmsiri, N., Najafi, F.: Fuzzy tuning of brain emotional learning based intelligent controllers. In: 2010 8th World Congress on Intelligent Control and Automation. IEEE, July 2010

13.

Jafari, M., Mohammad Shahri, A., Hamid Elyas, S.: Optimal tuning of brain emotional learning based intelligent controller using clonal selection algorithm. In: ICCKE 2013. IEEE, October 2013

14.

Valizadeh, S., Jamali, M.-R., Lucas, C.: A particle-swarm-based approach for optimum design of BELBIC controller in AVR system. In: International Conference on Control, Automation and Systems, COEX, Seoul, Korea, pp. 2679–2684, October 2008

15.

Valipour, M.H., Maleki, K.N., Ghidary, S.S.: Optimization of emotional learning approach to control systems with unstable equilibrium. In: Lee, R. (ed.) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. SCI, vol. 569, pp. 45–56. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-10389-1_4CrossRef

16.

El-Saify, M.H., El-Garhy, A.M., El-Sheikh, G.A.: Brain emotional learning based intelligent decoupler for nonlinear multi-input multi-output distillation columns. Math. Probl. Eng. 1–13, 2017 (2017)

17.

Mei, Y., Tan, G., Liu, Z.: An improved brain-inspired emotional learning algorithm for fast classification. Algorithms 10(2), 70 (2017)MathSciNetCrossRef

18.

César, M.B., Coelho, J.P., Gonalves, J.: Evolutionary-based bel controller applied to a magneto-rheological structural system. Actuators 7(2), 29 (2018)CrossRef

19.

Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceedings of the 1995 IEEE International Conference on Neural Network, pp. 1942–1948 (1995)

20.

Shi, Y., Eberhart, R.C.: Parameter selection in particle swarm optimization. In: Porto, V.W., Saravanan, N., Waagen, D., Eiben, A.E. (eds.) EP 1998. LNCS, vol. 1447, pp. 591–600. Springer, Heidelberg (1998). https://doi.org/10.1007/BFb0040810CrossRef

Titel: BELBIC Based Step-Down Controller Design Using PSO
verfasst von: João Paulo Coelho
Manuel Braz-César
José Gonçalves
Verlag: Springer International Publishing
Buch: Optimization, Learning Algorithms and Applications
Print ISBN: 978-3-030-91884-2

Electronic ISBN: 978-3-030-91885-9

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-91885-9_25

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner