PI-controller tuning optimization via PSO-based technique

• Autorzy: Romasevych Yuriy , Loveikin Viatcheslav , Usenko Sergii

Identyfikatory

DOI

10.15199/48.2019.07.08

Warianty tytułu

PL

Optymalizacja sterownika PI bazująca na algorytmach PSO

• Języki publikacji: EN

Abstrakty

EN

The technique of PI-controller tuning, which is based on a modification of the particle swarm optimization method, has been developed in the article. In order to take into account the most important quality indicators of plant controlling the complex criterion was developed. PI-controller tuning procedure has been reduced to the problem of criterion minimization. In the article, five benchmark transfer functions were used to estimate the technique. Comparative analysis with other well-known tuning techniques revealed the superiority of the proposed approach.

PL

W artykule przedtawiono metodę optymalizacji sterownika PI wykorzystującą algorytm rojowy. W artykule przedstawiono pięć rezultatów testów oraz porównanie tej metody z innymi powszechnie stosowanymi.

Słowa kluczowe

EN

PI controller; particle swarm optimization (PSO); tuning; criterion

PL

sterowniki PI; optymalizacja; algorytm PSO

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2019
• Tom: R. 95, nr 7
• Strony: 33--37
• Opis fizyczny: Bibliogr. 23 poz., rys., tab.

Twórcy

autor

Romasevych Yuriy

• National University of Life and Environmental Sciences of Ukraine, Geroiv Oborony str. 12 v, Ukraine

autor

Loveikin Viatcheslav

• National University of Life and Environmental Sciences of Ukraine, Geroiv Oborony str. 12 v, Ukraine

autor

Usenko Sergii

• National University of Life and Environmental Sciences of Ukraine, Geroiv Oborony str. 12, Ukraine

Bibliografia

• [1] O’Dwyer Handbook of PI and PID controller tuning rules (3rd edition). Ireland: Imperial College Press (2009), p. 623.
• [2] Anil Kumar , Rajeev Gupta, Tuning Of PID Controller Using PSO Algorithm And Compare Results Of Integral Errors For AVR System, International journal of innovative research and development, (2013), Vol 2, Issue 4, 58-68.
• [3] K.Lakshmi Sowjanya, l. Ravi Srinivas, Tuning of PID controllers using particle swarm optimization, InternationalJournal of Industrial Electronics and Electrical Engineering, (2015), Vol 3, Issue 2, 17-22.
• [4] Mahmud Iwan Solihin, Lee Fook Tack and Moey Leap Kean, Tuning of PID Controller Using Particle Swarm Optimization (PSO), Proceeding of the International Conference on Advanced Science, Engineering and Information Technology, (2011), 458-461.
• [5] Bassi S. J., Mishra M.K., Omizegba E.E., Automatic tuning of proportional–integral–derivative (PID) controller using particle swarm optimization (PSO) algorithm International Journal of Artificial Intelligence & Applications (IJAIA), (2011), Vol.2, No.4, 25-34.
• [6] Aekarin Sungthonga, Wudhichai Assawinchai choteb, Particle Swarm Optimization based Optimal PID Parameters for Air Heater Temperature Control System, Procedia Computer Science 86, (2016), 108-111.
• [7] Mehdi Nasri, Hossein Nezamabadi -pour, and Malihe Maghfoori, A PSO-Based Optimum Design of PID Controller for a Linear Brushless DC Motor, International Science Index, Electrical and Information Engineering, (2007), Vol 1, No 2, 179-183.
• [8] Aranza M.F. , Kustija J., Trisno B. and Hakim D.L., Tunning PID controller using particle swarm optimization algorithm on automatic voltage regulator system, International Conference on Innovation in Engineering and Vocational Education. IOP Conf. Series: Materials Science and Engineering 128, (2016), 1-9.
• [9] Ansu Elizabeth Kurian, Koshy Thomas, Comparison of Adaptive PID controller and PSO tuned PID controller for PMSM Drives, International Journal of Advance Engineering and Research Development, (2018), Vol 5, Issue 03, 812-820.
• [10] Jau-Woei Perng, Guan-Yan Chen, Shan-Chang Hs ieh, Optimal PID Controller Design Based on PSO-RBFNN for Wind Turbine Systems, Energies (2014), 7, 191-209.
• [11] Mercy D., Gir iraj kumar S.M., Design of PSO-PID controller for a nonlinear conical tank process used in chemical industries, ARPN Journal of Engineering and Applied Sciences, (2016), Vol. 11, No. 2, 1147-1153.
• [12] Latha K., Rajinikanth V., Surekha, P.M., PSOBased PID Controller Design for a Class of Stable and Unstable Systems, ISRN Artificial Intelligence, (2013), 1-11.
• [13] Hoda Pourhossein, Assef Zare, Mohammad Monfared, Hybrid Modeling and PID-PSO Control of Buck-Boost Chopper, Przegląd elektrotechniczny, (2012), 88(8), 187-191.
• [14] Romasevych Yu. , Loveikin V. A Novel Multi-Epoch Particle Swarm Optimization Technique, Cybernetics and Information Technologies, (2018), 18(3), 62-74.
• [15] Ziegler J .G. , Nichols N.B. , Optimum Settings for Automatic Controllers, Transaction of the ASME, (1942), Vol. 64, 759-768.
• [16] Åström K.J., Hägglund T. PID Controllers: Theory, Design and Tuning, Instrument Society of America NC.: Research Triangle Park, 2 edition, (1995), p. 344.
• [17] Åström K. J . , Hägglund T., Revisiting the Ziegler-Nichols step response method for PID control, Journal of Process Control, (2004), 14, 635-650.
• [18] Chien K.L., Hrones J.A. , Reswick J.B., On the automatic control of generalized passive systems, Transaction of the ASME, (1952), Vol. 74, No.2, 175- 185.
• [19] Cohen G.H., Coon G.A., Theoretical Consideration of Retarded Control, Transaction of the ASME, (1953), Vol. 75, 827-834.
• [20] Eriksson L., Control Design and Implementation of Networked Control Systems. Licentiate thesis’ Department of Automation and Systems Technology, Helsinki University of Technology, (2008), 118.
• [21] Skogestad S., Simple analytic rules for model reduction and PID controller tuning, J. Process Control, (2003), 13(4), 291-309.
• [22] Luyben W.L, Luyben M.L., Essentials of Process Control, (1997), McGraw-Hill.
• [23] Åströn K.J., Hägglund T., Benchmark Systems for PID Control / International Federation of Automatic Control, (2000), 165-166.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).