JRM Vol.28 No.5 pp. 739-744
doi: 10.20965/jrm.2016.p0739


Virtual Reference Feedback Tuning for Cascade Control Systems

Huy Quang Nguyen*, Osamu Kaneko**, and Yoshihiko Kitazaki*

*Graduate School of Natural Science and Technology, Kanazawa University
Kakuma-machi, Kanazawa, Ishikawa 920-1192, Japan

**Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications
1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan

March 31, 2016
July 19, 2016
October 20, 2016
virtual reference feedback tuning (VRFT), cascade control system, data-driven approach

Virtual Reference Feedback Tuning for Cascade Control Systems

Data-driven approach to cascade control systems

Virtual Reference Feedback Tuning (VRFT), proposed by Campi et al., is an effective data-driven tuning method used in feedback controllers because the desired parameters implemented in the controller are obtained by using only one-shot experiment data. In this paper, we apply VRFT to cascade control systems. We also discuss the meaning of the cost function to be minimized. A numerical example is demonstrated to show an effectiveness and validity of our proposed method.

Cite this article as:
H. Nguyen, O. Kaneko, and Y. Kitazaki, “Virtual Reference Feedback Tuning for Cascade Control Systems,” J. Robot. Mechatron., Vol.28, No.5, pp. 739-744, 2016.
Data files:
  1. [1] I. Al-Abbas, “Methodical tuning of proportional plus integral controllers for cascade control of separately excited DC motors,” American J. of Applied Sciences, Vol.9, No.11, pp. 1891-1898, 2012.
  2. [2] A. S. Abd Elhamid, “Cascade control system of direct current motor,” World Applied Sciences J., Vol.18, No.12, pp. 1680-1688, 2012.
  3. [3] Anagha et al., “Cascade speed control of DC motor,” Int. J. of Electrical, Electronics and data communication, Vol.2, Issue 6, pp. 78-81, 2014.
  4. [4] R. Bhavina, “Cascade control of DC motor with advance controller,” Int. J. of Industrial Electronics and Electrical Engineering, Vol.1, Issue 1, pp. 18-20, 2013.
  5. [5] H. Hjalmarsson, M. Gevers, S. Gunnarsson, and O. Lequin, “Iterative feedback tuning: Theory and applications,” IEEE Control Systems Magazine, Vol.18, No.4, pp. 26-41, 1998.
  6. [6] S. Souma, O. Kaneko, and T. Fujii, “A new method of a controller parameter tuning based on input-output data: Fictitious reference iterative tuning,” Proc. of the 8th IFAC Workshop on Adaptation and Learning in Control and Signal Processing, pp. 789-794, 2004.
  7. [7] O. Kaneko, “Data-Driven Controller Tuning: FRIT Approach,” Proc. of the 2nd IFAC Workshop on Adaptation and Learning in Control and Signal Processing, pp. 326-336, 2013.
  8. [8] G. O. Guardabassi and S. M. Savaresi, “Virtual reference direct design method: an off-line approach to data-based control system design,” IEEE Trans. Automatic Control, Vol.45, No.5, pp. 954-959, 2000.
  9. [9] M. C. Campi, A. Lecchini, and S. M. Savaresi, “Virtual reference feedback tuning: a direct method for the design of feedback controllers,” Automatica, Vol.38, Issue 8, pp. 1337-1346, 2002.
  10. [10] A. Lecchini, M. C. Campi, and S. M. Savaresi, “Virtual reference feedback tuning for two degree of freedom controllers,” Int. J. Adapt. Control and Signal Process, Special issue on controller design, Vol.16, No.5, pp. 355-371, 2002.
  11. [11] H. T. Nguyen and O. Kaneko, “Fictitious reference iterative tuning for cascade control systems,” SICE Annual Conf., pp. 774-777, 2015.
  12. [12] H. T. Nguyen and O. Kaneko, “Fictitious Reference Iterative Tuning for Cascade PI Controllers of DC Motor Speed Control Systems,” IEEJ Trans. on Electronics, Information and Systems, Vol.136, No.5, pp. 710-714, 2016.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Dec. 01, 2020