Journal of Applied Science and Engineering

Published by Tamkang University Press

1.30

Impact Factor

1.60

CiteScore

Yin-Tien Wang This email address is being protected from spambots. You need JavaScript enabled to view it.1 and Sung-Lin Wu1

1Mechanical Engineering Department, Tamkang University, Tamsui, Taiwan 251, R.O.C.


 

Received: July 28, 2005
Accepted: October 25, 2005
Publication Date: June 1, 2006

Download Citation: ||https://doi.org/10.6180/jase.2006.9.2.07  


ABSTRACT


In this paper, a new approach is proposed to model and control the temperature of a thermal barrel of a plastic molding machine. Usually the thermal barrel behavior is expressed in terms of a parameterized linear model to be used in control strategies design. We establish a new model based on the structure of a Takagi-Sugeno fuzzy system, and utilize the clustering method to generate the rule base of the fuzzy system. The proposed methodology is shown to be more effective than a conventional method in constructing system models. Meanwhile, the developed fuzzy model may provide a more accurate output prediction than conventional linear models suggested in the literature. In order to evaluate the control performance, the thermal models are integrated into the Internal Model Controller to control the temperature of a thermal barrel. The system is subjected to a step input and the responses depict the control performance of the models. The fuzzy model shows excellent performance in the step response, while the linear model has an oscillatory output at steady state. The proposed fuzzy model has the capability of application to control temperature in a plastic molding process.


Keywords: Fuzzy Systems, Thermal Control, Multivariable Control


REFERENCES


  1. [1] Kirby, R. B. “Process Dynamics of Screw Extruders,” Society of Plastics Engineering Journal, Vol. 18, pp. 12731281 (1962).
  2. [2] Krueger, W. L. “Experimental Illustrations of Dynamic Extrusion Theory,” Society of Plastics Engineering Journal, Vol. 18, pp. 12821287 (1962).
  3. [3] Reber, D. H., Lynn, R. E. and Frech, E. J., “A Mathematical Model for Predicting Dynamic Behavior of a Plastic Extruder,” Polymer Engineering and Science, Vol. 13, pp. 346356 (1973).
  4. [4] Tsai, C.-C. and Lu, C.-H., “Multivariable Self-Tuning Temperature Control for Plastic Injection Molding Process,” IEEE Transactions on Industry Applications, Vol. 34, pp. 310318 (1998).
  5. [5] Kochhar, A. K. and Parnaby, J. “Dynamical Modeling and Control of Plastics Extrusion Processes,” Automatica, Vol. 13, pp.177183 (1977).
  6. [6] Sugeno, M. and Kang, G. T., “Structure Identification of Fuzzy Model,” Fuzzy Sets and Systems, Vol. 28, pp. 1533 (1988).
  7. [7] Takagi, G. T. and Sugeno, M., “Fuzzy Identification of Systems and its Applications to Modeling and Control,” IEEE Transactions on Systems, Man and Cybernation, Vol. 15, pp. 116132 (1985).
  8. [8] Wang, L. X., A Course in Fuzzy System and Control, Prentice-Hall (1997).
  9. [9] Wong, C. C. and Chen, C. C. “A Clustering-Based Method for Fuzzy Modeling,” IEICE Transaction on Information and System, Vol. E82-D, pp. 10581065 (1999).
  10. [10] Seaman, C. M., Desrochers, A. A. and List, G. F., “Multiobjectvie Optimization of a Plastic Injection Molding Process,” IEEE Transactions on Control Systems Technology, Vol. 2, pp. 157168 (1994).
  11. [11] Fang, K. and Yao, L., “Application of Multivariable Fuzzy Control in Heating System of Injection Moulding Machine,” Proceedings of the IEEE International Conference on Industrial Technology, pp. 603606 (1996).
  12. [12] Zheng, F. J., Shi, F., Feng, X. G., Zhou, C. M. and Liu, Z. Q., “A Real-time Fuzzy Control for a Kind of Multivariable Object,” Proceedings of the IEEE International Conference on Industrial Technology, pp. 617 620 (1996).
  13. [13] Wang, S. J., Hwu, W. C. and Wang, Y. T. “Pressure and Temperature Control for a Thermal Barrel of the Plastic Extrusion Process,” National Conference on Automatic Technology, Taiwan (1999). (in Chinese)
  14. [14] Sousa, J. M., Babuska, R. and Verbruggen, H. B., “Internal Model Control with a Fuzzy Model: Application to an Air-Conditioning System,” Fuzzy Systems, Vol. 1, pp. 207212 (1997).
  15. [15] Strang, G., Linear Algebra and Its Applications, Second edition, Academic Press (1980).
  16. [16] Phillips, C. L. and Nagle, H. T. Digital Control System Analysis and Design, 3rd Ed, Prentice Hall (1995).
  17. [17] Advantech, PCL-818HG six-channel D/A output card user’s manual (1994).
  18. [18] Advantech, PCL-836 interface card user’s manual (1994).