A METHOD TO DESIGN PID CONTROLLERS USING FRIT-PSO

Publications

Share / Export Citation / Email / Print / Text size:

International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering , Engineering, Electrical & Electronic

GET ALERTS

eISSN: 1178-5608

DESCRIPTION

4
Reader(s)
4
Visit(s)
0
Comment(s)
0
Share(s)

VOLUME 8 , ISSUE 4 (December 2015) > List of articles

A METHOD TO DESIGN PID CONTROLLERS USING FRIT-PSO

Takehito Azuma *

Keywords : PID control, feedback control systems, iterative methods, fictitious reference iterative tuning, particle-swarm optimization, DC motors.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 8, Issue 4, Pages 1,876-1,895, DOI: https://doi.org/10.21307/ijssis-2017-834

License : (CC BY-NC-ND 4.0)

Received Date : 14-September-2015 / Accepted: 10-November-2015 / Published Online: 01-December-2015

ARTICLE

ABSTRACT

This paper proposes the Fictitious Reference Iterative Tuning-Particle Swarm Optimization (FRIT-PSO) method to design PID controllers for feedback control systems. The proposed method is an offline PID parameter tuning method. Moreover it is not necessary to derive any mathematical models of objected control systems. The proposed method is demonstrated by comparing with the FRIT method in numerical examples and an experiment.

Content not available PDF Share

FIGURES & TABLES

REFERENCES

[1] P. Kundur, “Power system stability and control”, McGraw-Hill, 1993.
[2] A. J. Wood, B. F. Wollenberg and G. B. Sheble, “Power generation, operation, and control”, Woley, 2013
[3] A. Visioli, “Practical PID Control”, Springer, 2006.
[4] K. L. Chien, J. A. Hrones and J. B. Reswick, “On the automatic control of generalized passive systems”, Transaction of American Society of Mechanical Enginnering, Vol. 74, pp. 827-834, 1952.
[5] G. H. Cohn and G. A. Coon, “Theoretical consideration of related control”, Transaction of American Society of Mechanical Enginnering, Vol. 75, pp. 827-834, 1953.
[6] T. Kailath, “Linear Systems”, Prentice-Hall., 1979.
[7] T. Kitamori, “A method of control system design based upon partial knowledge about controlled processess”, Transactions of the Society of Instrument and Control Engineers, Vol. 15, No. 4, pp. 549-555, 1979.
[8] S. Bennett, “Development of the PID controller,” IEEE Control Systems, Vol. 13, No.6, pp. 58-62, 1993.
[9] K. J. Astrom and T. Hagglund, “PID controllers: theory, design, and tuning”, Research Triangle, 1995.
[10] G. F. Franklin, J. D. Powell and A. Emami-Naeni, “Feedback control of dynamical systems”, Prentice-Hall, 2002.
[11] T. Hagglund and K. J. Astrom, “Revisiting the Ziegler–Nichols step response method for PID control”, Journal of Process Control, Vol. 14, pp. 635–650, 2004.
[12] M. W. Foley, R. H. Julien and B. R. Copeland, “A comparison of PID controller tuning methods”, The Canadian Journal of Chemical Engineering, Vol. 83, No. 4, pp. 712-722, 2008.
[13] S. C. Mukhopadhyay, T. Ohji, M. Iwahara, S. Yamada and F. Matsumura, “Disturbance attenuation and h-infinity control on repulsive type magnetic bearing”, IEEE Transactions on Magnetics, Vol. 33, No. 5, pp. 4233-4235, 1997.
[14] S. C. Mukhopadhyay, T. Ohji, M. Iwahara, S. Yamada and F. Matsumura, “Permanent magnet configuration in repulsive type magnetic bearing for improved disturbance attenuation characteristics”, COMPEL-International Journal for Computation and Mathematics in Electrical and Electronics Engineering, Vol. 17, pp. 290-295, 1998.
[15] S. C. Mukhopadhyay, T. Ohji, M. Iwahara, S. Yamada and F. Matsumura, “Design and development of a low cost repulsive type magnetic bearing and its h-infinity control”, Journal of Non-linear Electromagnetic Systems, IOS Press, 13, 741-744, 1998.
[16] K. J. Astrom, H. Panagopoulos and T. Hagglund, “Design of PI controllers based on non-convex optimization”, Automatica, Vol. 34, No. 5, pp. 585-601, 1998.
[17] M. Hast, K. Astrom, M. Hast, K. J.Astrom, B. Bernhardsson and S. Boyd, “Design by convex-concave optimization”, Proceedings of 2013 European Control Conference, pp. 4460-4465, 2013.
[18] H. Hjalmarsson, M. Gevers, S. Gunnarsson and O. Lequin, “Iterative feedback tuning: theory and applications”, IEEE Control Systems, Vol. 18, No. 4, pp. 26-41, 1998.
[19] G. O. Guardabassi and S. M. Savaresi, “Virtual reference direct design method: an off-line approach to data-based control system design”, IEEE Transaction on Automatic Contol, Vol. 45, No. 5, pp. 954-959, 2000.
[20] H. Hjalmarsson, “Iterative feedback tuning – an overview”, International Journal of Adaptive Control and Signal Processing, Vol. 16, pp. 373-395, 2002.
[21] M. C. Campi, A. Lecchini and S. M. Savaresi, “Virtual reference feedback tuning(VRFT): a direct method for the design of feedback controllers”, Automatica, Vol. 38, pp. 1337-1346, 2002.
[22] M. C. Campi and S. Savaresi, “Direct nonlinear control design: the virtual reference feedback tuning(VRFT) approach”, IEEE Transaction on Automatic Contol, Vol. 51, No. 1, pp. 14-27, 2006 .
[23] S. Arimoto, S. Kawamura and F. Miyazaki, “Bettering operation of robots by learning”, Journal of Robotic Systems, Vol. 1, No. 2, pp. 123-140, 1984.
[24] J. Moon, T. Doh and M. J. Chung, “An iterative learning control design approach for networked control systems with data dropouts”, International Journal of Robust and Nonlinear Control, Vol. 34, No. 8, pp. 1001-1004, 1998.
[25] H. Ahn, Y. Q. Chen and K. L. Moore, “Iterative learning control: brief survey and categorization”, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, Vol. 37, No. 6, pp. 1099 – 1121, 2007.
[26] D. P. Bertsekus, “Nonlinear Programming”, Athena Scientific, 1999.
[27] D. P. Bertsekus, “Dynamic programming and optimal control”, Third edition, Athena Scientific, 2005
[28] S. Soma, O. Kaneko and T. Fujii, “A new approach to parameter tuning of controllers by using one-shot experimental data – a proposal of fictitious reference iterative tuning”, Transactions of the institute of systems, control and information engineers, Vol. 17, No. 12, pp. 528-536, 2004.
[29] O. Kaneko, Y. Yamashina and S. Yamamoto, "Fictitious reference tuning of the feed-forward controller in a two-degree-of-freedom control system", SICE Journal of Control Measurement and System Integration, Vol. 4, No. 1, pp. 55-62, 2011.
[30] J. Kennedy and R. Eberhart, “Particle swarm optimization”, Proceedings of IEEE international conference on neural networks, Vol. 4, pp. 1942-1948, 1995.
[31] T. Azuma and S. Saijo, “Development and experiment of networked control systems with congestion control”, In S. C. Mukhopadhyay(Eds.), Smart Sensors and Sensing Technology,Lecture Notes in Electrical Engineering, pp. 15-27, Springer-Verlag, 2008.
[32] T. Azuma, “Design and experimental verification of state predictive LQG controllers for networked control systems”, International Journal on Smart Sensing and Intelligent Systems, Vol. 7, No. 3, pp. 1201-1220, 2014.
[33] M. Banzi, Getting Started with Arduino, Maker Media, Inc., 2011.
[34] G. Ueno, K. Yasuda and N. Iwasaki, “Robust-adaptive particle swarm optimization”, Proceedings of IEEE International Conference on Systems, Man and Cybernetics, Vol. 4, pp. 3915-3920, 2005.

EXTRA FILES

COMMENTS