IMPROVING OPTIMAL CONTROL OF GAS PUMPING UNIT BASED ON MULTIVARIABLE REGULATOR
Keywords:
regulator, centrifugal supercharger, setting, transmission function, operation speed.Abstract
operation of the centrifugal pumping unit supercharger (BH SBS) with fuzzy regulators was analyzed. The technique for constructing fuzzy PI and PID regulators was suggested. Modeling of the technological process was conducted on the basis of the block diagrams developed in Matlab software product and rule databases formed in the Fuzzy Logic Toolboxes for the regulators under study. The comparative analysis of the transient processes with
the relevant regulators was carried out.
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References
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3 Новак В. Математические принципы нечеткой логики / В. Новак, И. Перфильева, И. Мочкрож. – М.: Физматлит, 2006. – 352 с.
4 Денисенко В. ПИД-регуляторы: принципы построения и модификации. Ч. 2. / В. Денисенко // Современные технологии автоматизации. – 2007. – №1. – С. 78-88.
5 Ang, K. H. PID control system analysis, design, and technology / K. H. Ang, G. Chong, Y. Li // IEEE Trans. on Control Syst. Tech, 2005. – Vol. 13, № 4. – P. 559–576.
6 O'Dwyer A. PID compensation of time delayed processes 1998-2002: a survey / A. O'Dwyer// Proceedings of the American Control Conference.Denver, 2003, p. 1494-1499.
7 Quevedo I. Digital control: past, present and future of PID control / I. Quevedo // Proceedings of the IFAC Workshop, Eds., Terrassa, Spain, 5 - 7 April 2000.
8 Astrom K. J. Advanced PID control / K. J. Astrom, T. Hagglund - ISA (The instrumentation, Systems, and Automation Society), 2006 - 460 p.
9 Li Y. Patents, software, and hardware for PID control / Y. Li, K. H. Ang, G. C. Y. Chong // An overviewand analysis of the current art. IEEE Control Systems Magazine. - 2006. - P. 41-54.
10 A. Leva, C. Hands-on PID autotuning: a guide to better utilisation / A. Leva, C. Cox, A. Ruano // IFAC Professional Brief, 2002.
11 Yesil E. Internal model control based fuzzy gain scheduling technique of PID controllers / E. Yesil, M. Guzelkaya, I. Eksin // World Automation Congress, 28 June - 1 July 2004. Proceedings. Vol. 17. P. 501-506.
12 Kato M. A skill-based PID controller using artificial neural networks / M. Kato, T. Yamamoto, S. Fujisawa// Computational Intelligence for Modeling, Control and Automation and International Conference on Intelligent Agents, Web
of Technologies and Internet Commerce, 28_30 Nov. 2005. Vol. 1. P. 702-707.
13 Kawafuku R. Self-tuning PID control of a flexible micro-actuator using neural networks / R. Kawafuku, M. Sasaki, S. Kato // IEEE International Conference on Systems, Man and Cybernetics, 11-14 Oct. 1998. Vol. 3. P. 3067-3072.
14 Pereira D.S. Genetic algorithm based system identification and PID tuning for optimum adaptive control / D.S. Pereira, J.O.P. Pinto// IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2005. Proceedings. P. 801-806.
15 Zadeh L.A. Fuzzy sets / L.A. Zadeh // Information and Control. 1965. № 8. P. 338 - 353.
16 Mamdani E.H. Application of fuzzy algorithm for simple dynamic plant / E.H. Mamdani // Proc. IEEE. 1974. № 12. P. 1585 - 1588.
17 Mann G.K.I. Analysis of direct action fuzzy PID controller structures / G.K.I. Mann, Hu Bao_Gang, R.G. Gosine // IEEE Transactions on Systems, Man and Cybernetics, Part B. Jun. 1999.Vol. 29. Issue 3. P. 371 - 388.
18 Feng H.-M. A self-tuning fuzzy control system design / H.-M. Feng // IFSA World Congress and 20th NAFIPS International Conference, 25_28 July 2001. Vol. 1. P. 209-214.
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Published
15.05.2015
How to Cite
Семенцов, Г. Н., & Лагойда, А. І. (2015). IMPROVING OPTIMAL CONTROL OF GAS PUMPING UNIT BASED ON MULTIVARIABLE REGULATOR. Oil and Gas Power Engineering, (1(23), 61–68. Retrieved from https://nge.nung.edu.ua/index.php/nge/article/view/336
Issue
Section
POWER ENGINEERING, CONTROL AND DIAGNOSTICS OF OIL AND GAS COMPLEX FACILITIES
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