JACIII Vol.11 No.9 pp. 1144-1148
doi: 10.20965/jaciii.2007.p1144


Generalized Predictive Control in Flying Shear Equipment

Jiun-Yaw Wang*, Mao-Lin Chen*,**, and Ching-Long Shih*

*Department of Electrical Engineering, National Taiwan University of Science and Technology, 43, Section 4, Keelung Road, Taipei, Taiwan 106

**Department of Electrical Engineering, Chien kuo Technology University, Chanwa, Taiwan

December 30, 2006
July 13, 2007
November 20, 2007
Generalized Predictive Control (GPC), PID control, flying-shear cutter
To develop and evaluate improved on-line flying-shear equipment control tasks, we introduces a Generalized Predictive Control (GPC) PID controller for positioning control of a flying-shear cutter. After successful trials and excellent regulation results, the GPC-based PID control algorithm with constraints is proved to be very robust.
Cite this article as:
J. Wang, M. Chen, and C. Shih, “Generalized Predictive Control in Flying Shear Equipment,” J. Adv. Comput. Intell. Intell. Inform., Vol.11 No.9, pp. 1144-1148, 2007.
Data files:
  1. [1] M. Mahfouf and D. A. Linkens, “Generalised Predictive Control (GPC) in Medicine,” IEE Colloquium on Adaptive Controllers in Practice, pp. 4/1-4/9, Nov. 2, 1995.
  2. [2] T. Yamamoto, J. Aoyama, and K. Nakano, “A Design of 2 DOF Robust Self-Tuning GPC,” IEEE International Symposium on Industrial Electronics 2003 (ISIE ’03), Vol.1, 9-11, pp. 566-571, June 2003.
  3. [3] M. Abu-Ayyad and R. Dubay, “Real-time Comparison of a Number of Predictive Controllers,” ISA Transactions, Vol.46, No.3, pp. 411-418, June 2007.
  4. [4] H. N. Koivo, “A Multivariable Self-tuning Controller,” Automatica, Vol.16, pp. 351-366, 1980.
  5. [5] L. Dugar, G. C. Goodwin, and X. Xianya, “The Role of the Interactor Matrix in Multivariable Stochastic Adaptive Control,” Automatica, Vol.20, pp. 701-709, 1984.
  6. [6] R. Scattolini, “A Multivariable Self-tuning Controller with Integral Action,” Automatica, Vol.22, pp. 619-627, 1986.
  7. [7] N. Peric and I. Petrovic, “Flying Shear Control System,” IEEE Trans. on Industry Applications, Vol.26, No.6, pp. 1049-1056, December 1990.
  8. [8] K. Bender, M. Pandit, and W. Weber, “Energy Optimal Rotating Shears Control,” Regelungstechnik und Prozess-Dotenverorbeitung, Vol.12, pp. 540-545, Jan. 1970 (in German).
  9. [9] W. Leonhard, “Control of Electrical Drives,” Berlin-Heidelberg-New York-Tokyo: Springer-Verlag, 1985.
  10. [10] W. Leonhard, “Time Optimal Flying Shear Control,” Archiv für Elektrotechnik, No.58, pp. 61-67, 1976 (in German).
  11. [11] M. Kinnaert, “Generalized Predictive Control for MIMO Linear Systems,” Analysis and Control of Nonlinear Systems, Elsevier Science Publishers B. V. (North-Holland), pp. 27-34, 1988.
  12. [12] M. Kinnaert, “Generalized Predictive Control of Multivariable Linear Systems,” 26th IEEE Conference on Decision and Control, 1987, Vol.26, Part 1, pp. 1247-1248, Dec. 1987.
  13. [13] M. Kinnaert, “Adaptive Control of Multiple-Input-Multiple-Output Linear System,” Doctorate Thesis, Universite Libre de Bruxelles, 1987 (in French).
  14. [14] D. W. Clarke, C. Mohtadi, and P. S. Tuffs, “Generalized Predictive Control-Part I and II,” Automatica, Vol.23, No.2, pp. 137-160, 1987.
  15. [15] K. Hayashi, A. Otsubo, and K. Shiranita, “Realization of PID Control by Fuzzy Inference and its Application to Hybrid Control,” Journal of Advanced Computational Intelligence, Vol.3, No.6, pp. 491-498, 1999.
  16. [16] C.-M. Chow, A. Kuznetsov, and D. Clarke, “Application of Multivariable Generalized Predictive Control to the Simulink Model of a Paper Machine,” Control Applications, Proc. of the 3rd IEEE Conference, Vol.3, pp. 1675-1681, 1994.
  17. [17] B. Su, Z. Chen, and Z. Yuan, “Constrained Predictive Control Based on T-S fuzzy Model for Nonlinear Systems,” Journal of Systems Engineering and Electronics, Vol.18, No.1, pp. 95-100, March 2007.

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

Last updated on Apr. 19, 2024