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Soft Computing

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31.08.2018 | Methodologies and Application

A particle swarm optimization, fuzzy PID controller with generator automatic voltage regulator

verfasst von: Abdullah J. H. Al Gizi

Erschienen in: Soft Computing | Ausgabe 18/2019

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Abstract

The role of an intelligent control system with a certain stage of autonomy is prerequisite for effective operation. We designed a particle swarm optimization, fuzzy proportional integral derivative (PSOFPID) controller using MATLAB for a set point voltage and frequency. The projected controller intended to ease the frequency and the terminal potential difference constantly under any operating conditions and loads which can be attained in the wanted range via the rule of the generation system. PSOFPID used to carry out the AVR system auctions main voltage control. The existing algorithm was based on particle swarm optimization (PSO), and Sugeno fuzzy logic (SFL). It required optimal tuning for thematic factory operation of the generation system. The newly developed controller combined the PSO and fuzzy logic control (FLC) to determine the optimal PID controller of generator parameters in the AVR system. The PSOFPID controller was used as a hybrid full control system for the voltage and frequency. Optimal PID gains obtained by a combined PSO and SFL for various operating conditions of PSO (β and know about birds’ no.) were employed to develop the principle subject of the Sugeno fuzzy system. The hybrid controller arranged the control signal based on communication and thereby decreases the voltage error and the swaying in the terminal voltage and frequency control process. An outstanding potential and frequency control presentation was achieved when the projected hybrid controller was broken on the AVR system in synchronous generator to improve the transient response.

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Al Gizi AJ, Mustafa M, Al-geelani NA, Alsaedi MA (2015) Sugeno fuzzy PID tuning, by genetic-neutral for AVR in electrical power generation. Appl Soft Comput 28:226–236CrossRef

Al-geelani NA, Afendi M, Piah M, Shaddad RQ (2012) Characterization of acoustic signals due to surface discharges on H.V. glass insulators using wavelet radial basis function neural networks. Appl Soft Comput 7(2):1327–1338

Arulmozhiyal R (2012) Design and implementation of fuzzy PID controller for BLDC motor using FPGA. In: IEEE international conference on power electronics, drives and energy systems (PEDES), 2012, 16–19 Dec 2012, pp 1–6

Arulmozhiyal R, Baskaran K (2009) Speed control of induction motor using fuzzy PI and optimized using GA. Int J Recent Trends Eng 2(5)

Arulmozhiyal R, Kandiban R (2012) Design of fuzzy PID controller for brushless DC motor. In: 2012 international conference on computer communication and informatics (ICCCI), 10–12 Jan 2012, pp 1–7

Barnes S, Maekawa S (2007) Generalization of Faraday’s law to include nonconservative spin forces. Phys Rev Lett 98(24):246601CrossRef

Chatterjee A, Ghoshal S, Mukherjee V (2011) Chaotic ant swarm optimization for fuzzy-based tuning of power system stabilizer. Int J Electr Power Energy Syst 33(3):657–672CrossRef

Chen W, Xing M, Fang K (2012) A PLC-based fuzzy PID controller for pressure control in Coke-oven. In: 2012 31st Chinese control conference (CCC), 25–27 July 2012, pp 4754–4758

Chen Z, Yuan X, Ji B, Wang P, Tian H (2014) Design of a fractional order PID controller for hydraulic turbine regulating system using chaotic non-dominated sorting genetic algorithm II. Energy Convers Manag 84:390–404CrossRef

Cui M (2012) Low carbon dispatch of distribution network containing microgrid using chaotic ant swarm. In: 2012 international conference on control engineering and communication technology (ICCECT), IEEE, pp 818–821

Devaraj D, Selvabala B (2009) Real-coded genetic algorithm and fuzzy logic approach for real-time tuning of proportional-integral—derivative controller in automatic voltage regulator system. Gener Transm Distrib IET 3(7):641–649. https://doi.org/10.1049/iet-gtd.2008.0287 CrossRef

Gaing ZL (2004) A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE Trans Energy Convers 19(2):384–391. https://doi.org/10.1109/TEC.2003.821821 CrossRef

Gozde H, Taplamacioglu MC (2011) Comparative performance analysis of artificial bee colony algorithm for automatic voltage regulator (AVR) system. J Frankl Inst 348(8):1927–1946. https://doi.org/10.1016/j.jfranklin.2011.05.012 MATHCrossRef

Guerrero JM, Chandorkar M, Lee T-L, Loh PC (2013) Advanced control architectures for intelligent microgrids, part I: decentralized and hierarchical control. IEEE Trans Ind Electron 60(4):1254–1262CrossRef

Gwo-Ruey Y, Rey-Chue H (2004) Optimal PID speed control of brush less DC motors using LQR approach. In: 2004 IEEE international conference on systems, man and cybernetics, 10–13 Oct 2004, vol 1, pp 473–478

Higgins N, Vyatkin V, Nair N-KC, Schwarz K (2011) Distributed power system automation with IEC 61850, IEC 61499, and intelligent control. IEEE Trans Syst Man Cybern C (Appl Rev) 41(1):81–92CrossRef

Jiang J (1995) Design of an optimal robust governor for hydraulic turbine generating units. IEEE Trans Energy Convers 10(1):188–194CrossRef

Jinwook K, Oh-Kyu C, Lee JS (2012) Design and stability analysis of TSK-type full-scale fuzzy PID controllers. In: 2012 IEEE international conference on fuzzy systems (FUZZ-IEEE), 10–15 June 2012, pp 1–8

Madinehi N, Shaloudegi K, Abedi M, Abyaneh HA (2011) Optimum design of PID controller in AVR system using intelligent methods. Power Tech, 2011 IEEE Trondheim. IEEE, 19–23 June 2011, pp 1–6

Man-chen X, Ling-long W (2012) Intelligent fuzzy- PID temperature controller design of drying system. In: 2012 International conference on information management, innovation management and industrial engineering (ICIII), 20–21 Oct 2012, pp 54–57

Minglin Y (2010) Realization of Fuzzy PID controller used in turbine speed control system with FPGA. 2010 international conference on future information technology and management engineering (FITME), 9–10 Oct 2010, pp 261–264

Mustafa M, Al Gizi AJ (2013) Hybrid neural-genetic and fuzzy logic approach for real-time tuning of PID controller to improve the system frequency response of AVR system. Life Sci J 10(4):2714–2724

Pan I, Das S (2012a) Chaotic multi-objective optimization based design of fractional order PIλDμ controller in AVR system. Int J Electr Power Energy Syst 43(1):393–407CrossRef

Pan I, Das S (2012b) Intelligent fractional order systems and control: an introduction. Springer, New YorkMATH

Pan I, Das S (2013) Frequency domain design of fractional order PID controller for AVR system using chaotic multi-objective optimization. Int J Electr Power Energy Syst 51:106–118. https://doi.org/10.1016/j.ijepes.2013.02.021 CrossRef

Pan I, Das S (2015) Fractional-order load-frequency control of interconnected power systems using chaotic multi-objective optimization. Appl Soft Comput 29:328–344CrossRef

Panda S, Sahu BK, Mohanty PK (2012) Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization. J Frankl Inst 349(8):2609–2625. https://doi.org/10.1016/j.jfranklin.2012.06.008 MathSciNetMATHCrossRef

Prasad LB, Gupta HO, Tyagi B (2014) Application of policy iteration technique based adaptive optimal control design for automatic voltage regulator of power system. Int J Electr Power Energy Syst 63:940–949CrossRef

Qasem SN, Shamsuddin SM (2011) Memetic elitist pareto differential evolution algorithm based radial basis function networks for classification problems. Appl Soft Comput 11(1):5565–5581CrossRef

Rahimian MS, Raahemifar K (2011) Optimal PID controller design for AVR system using particle swarm optimization algorithm. In: 2011 24th Canadian conference on electrical and computer engineering (CCECE), 8–11 May 2011, pp 000337–000340

Rajasekhar A, Jatoth RK, Abraham A (2014) Design of intelligent PID/PI λ D μ speed controller for chopper fed DC motor drive using opposition based artificial bee colony algorithm. Eng Appl Artif Intell 29:13–32CrossRef

Ramezanian H, Balochian S, Zare A (2013) Design of optimal fractional-order PID controllers using particle swarm optimization algorithm for automatic voltage regulator (AVR) system. J Control Autom Electr Syst 5(24):601–611CrossRef

Sahib MA (2015) A novel optimal PID plus second order derivative controller for AVR system. Eng Sci Technol Int J 18(2):194–206CrossRef

Shamisa A, Karrari M, Malik OP (2008) Power system transient stability assessment using on-line measurement data. Int Rev Electr Eng 3(4):653–661

Shivakumar R, Lakshmipathi R, Panneerselvam M (2010) Power system stability enhancement using bio inspired genetic and PSO algorithm implementation. Int Rev Electr Eng 5(4):1609–1615

Simoes MG, Bose BK, Spiegel RJ (1997) Fuzzy logic based intelligent control of a variable speed cage machine wind generation system. IEEE Trans Power Electron 12(1):87–95CrossRef

Sinthipsomboon K, Hunsacharoonroj I, Khedari J, Pongaen W, Pratumsuwan P (2011) A hybrid of fuzzy and fuzzy self-tuning PID controller for servo electro-hydraulic system. In: 2011 6th IEEE conference on industrial electronics and applications (ICIEA), 21–23 June 2011, pp 220–225

Soundarrajan A, Sumathi S (2010) Fuzzy-based intelligent controller for power generating systems. J Vib Control. https://doi.org/10.1177/1077546310371347 MATHCrossRef

Su H, Hao G, Li P, Luo X (2010) Feed forward fuzzy PID controller for common-rail pressure control of diesel engine. In: 2010 international conference on measuring technology and mechatronics automation (ICMTMA), 13–14 March 2010, pp 264–267

Tang Y, Cui M, Hua C, Li L, Yang Y (2012) Optimum design of fractional order PIλDμ controller for AVR system using chaotic ant swarm. Expert Syst Appl 39(8):6887–6896CrossRef

Vural AM, Bayindir KC (2012) Transient stability enhancement of the power system interconnected with wind farm using generalized unified power flow controller with simplex optimized self-tuning fuzzy damping scheme. Int Rev Electr Eng 7(4):5091–5107

Wahab NIA, Mohamed A (2010) Transient stability emergency control using generator tripping based on tracking area-based rotor angle combined with UFLS. Int Rev Electr Eng 5(5):2317–2326

Wong C-C, An LS, Wang H-Y (2009) Optimal PID controller design for AVR system. Tamkang J Sci Eng 12(3):259–270

Yao-Lun L, Chia-Chang T, Wu-Shun J, Shuen-Jeng L (2007) Design an intelligent neural-fuzzy controller for hybrid motorcycle. In: Fuzzy information processing society, 2007. NAFIPS ‘07. Annual meeting of the North American, 24–27 June 2007, pp 283–288

Yeroğlu C, Ateş A (2014) A stochastic multi-parameters divergence method for online auto-tuning of fractional order PID controllers. J Frankl Inst 351(5):2411–2429MathSciNetMATHCrossRef

Yu GR, Hwang RC (2004) Optimal PID speed control of brushless DC motors using LQR approach. In: IEEE international conference system, man, and cybernetics, pp 473–478

Zeng G-Q, Chen J, Dai Y-X, Li L-M, Zheng C-W, Chen M-R (2015) Design of fractional order PID controller for automatic regulator voltage system based on multi-objective extremal optimization. Neurocomputing 160:173–184CrossRef

Zhang Xiao M, Long Shi Y (2012) Simulation study on fuzzy PID controller for DC motor based on DSP. In: 2012 international conference on industrial control and electronics engineering (ICICEE), 23–25 Aug 2012, pp 1628–1631

Titel: A particle swarm optimization, fuzzy PID controller with generator automatic voltage regulator
verfasst von: Abdullah J. H. Al Gizi
Publikationsdatum: 31.08.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 18/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-018-3483-4

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