Particle swarm optimization for tuning PSS-PID controller of synchronous generator

• Autorzy: Derrar A. , Naceri A.

Identyfikatory

DOI

10.14313/JAMRIS_1-2017/6

• Języki publikacji: EN

Abstrakty

EN

In this paper the design an optimal PSS-PID controller for single machine connected to an infinite bus (SMIB). We presented a novel application of particle swarm optimization (PSO) for the optimal tuning of the new PSS-PID controller. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The synchronous generator is modeled and the PSO algorithm is implemented in Simulink of Matlab. The obtained results have proved that (PSO) are a powerful tools for optimizing the PSS parameters, and more robustness of the system IEEE SMIB.

Słowa kluczowe

EN

synchronous generator; PSS; particle swarm optimization (PSO); PID controller

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2017
• Tom: Vol. 11, No. 1
• Strony: 48--52
• Opis fizyczny: Bibliogr. 9 poz., rys.

Twórcy

autor

Derrar A.

• IRECOM Laboratory, Department of Electrical Engineering UDL – SBA University, BP 98, Sidi Bel Abbes – 22000, Algeria

autor

Naceri A.

• IRECOM Laboratory, Department of Electrical Engineering UDL – SBA University, BP 98, Sidi Bel Abbes – 22000, Algeria

Bibliografia

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• [2] C. H. Chen, S. N. Yeh, “Particle Swarm Optimization for Economic Power Dispatch with Valve-Point Effects”. In: IEEE PES Transmission and Distribution Conference and Exposition Latin America, Venezuela 2006. DOI: 10.1109/TDCLA. 2006.311397.
• [3] Ahmed Sabah Al-Araji, “Applying Cognitive Methodology in Designing On-Line Auto-Tuning Robust PID Controller for the Real Heating System”, Journal of Engineering, vol. 20, no. 9, September 2014, 43–61.
• [4] Fadhil A. Hassan, Lina J. Rashad, “Particle Swarm Optimization for Adapting Fuzzy Logic Controller of SPWM Inverter Fed 3-Phase I.M”, Eng. & Tech. Journal, vol. 29, no. 14, 2011, 2912–2925.
• [5] Fadel Mohammed , Bassam Abdelelah Kidher Mahmood, “Design of Fractional Order PID Controller Based Particle SWARM”, Diyala Journalof Engineering Sciences, vol. 7, no. 4, December 2014, 24–39.
• [6] Jin-Kao Hao, Philippe Galinier, Michel Habib, “Méthaheuristiques pour l’optimisation combinatoire et l’affectation sous contraintes”, LERIA, U.F.R. Sciences, Université d’Angers, 2 bd Lavoisier, 49045 Angers. Avalaible at : http://www.info. univ-angers.fr/pub/hao/papers/RIA.pdf.
• [7] D. E. Ghourad et al., “Exploitation des techniques fréquentielles avancées dans le contrôle automatique d’excitation des machines synchrones”, Journal of Advanced Research in Science and Technology, 2014, 1(2), 58–77.
• [8] K.E. Khoshmardan, M.R.Dastranj, M.O. Taleghani, A. Hajipoor, “Design a Fuzzy Logic Based Speed Controller for DC Motor with Particle Swarm Optimization “PSO” Algorithm”, Australian Journal of Basic and Applied Sciences.Azad University, Sabzevar, Iran.2011, 1283–1290.
• [9] C. Thanga, S.P. Snvastava, P. Agarwal, “Particle Swarm and Fuzzy Logic Based Optimal Energy Control of Induction Motor for a Mine Hoist Load Diagram”, IAENG International Journal of Computer Science, vol. 36, no. 1, 2009.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).