Control of Multi-variable Processes Using Self-Tuning Fuzzy

Majlesi Journal of Electrical Engineering

مقاله 5، دوره 10، شماره 1، خرداد 2016   

نوع مقاله: Review Article

نویسندگان

Abdolrahman Ramezani؛ Abdolah Rahimi^* ؛ Alireza Roosta

Faculty of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz

چکیده

Many industrial processes are Multi-Input Multi-Output (MIMO) that has more than one controlled variable. Therefore, without considering the impact of these factors it is not possible to achieve the desired performance. In this paper, two methods, adaptive controller and self-tuning fuzzy PID controller is used to control the quadruple-tank process. Although the both presented methods are able to eliminate disturbance effect and reach steady-state with acceptable performance, the fuzzy controller is preferred to the adaptive controller due to the lower computational effort. Moreover, the fuzzy controller does not need the transfer function of the system, while it has a simple design procedure and simple arithmetic. Superiority of the proposed method is automatic adjustment of multivariable fuzzy controller parameters to achieve desirable performance.

کلیدواژه‌ها

Self-tuning fuzzy controller؛ en؛ Adaptive controller؛ multi-variable systems؛ Recursive Least Square؛ relative gain arrays

مراجع

[1] F. Zheng, et al., "On the design of multivariable PID controllers via LMI approach," Automatica, vol. 38, pp. 517-526, 2002.

[2] R. K. Mudi and N. R. Pal, "A robust self-tuning scheme for PI-and PD-type fuzzy controllers," Fuzzy Systems, IEEE Transactions on, vol. 7, pp. 2-16, 1999.

[3] S. P. Bhattacharyya, et al., Robust control: Prentice-Hall Upper Saddle River, New Jersey, 1995.

[4] C. Batur and V. Kasparian, "Adaptive expert control," International Journal of Control, vol. 54, pp. 867-881, 1991.

[5] E. Davison, "Multivariable tuning regulators: the feedforward and robust control of a general servomechanism problem," Automatic Control, IEEE Transactions on, vol. 21, pp. 35-47, 1976.

[6] G. H. Ellis, Control system design guide: a practical guide: Academic Press, 2004.

[7] W. Jian and C. Wenjian, "Development of an adaptive neuro-fuzzy method for supply air pressure control in HVAC system," 2000, pp. 3806-3809 vol. 5.

[8] K. J. Astrom, "Oscillations in systems with relay feedback," The IMA Volumes in Mathematics and its Applications: Adaptive Control, Filtering and Signal Processing, vol. 74, pp. 1-25, 1995.

[9] J. M. Maciejowski, "Multivariable feedback design," Electronic Systems Engineering Series, Wokingham, England: Addison-Wesley,| c1989, vol. 1, 1989.

[10] G. C. Shen and W. K. Lee, "Multivariable adaptive inferential control," Industrial & Engineering Chemistry Research, vol. 27, pp. 1863-1872, 1988.

[11] K. M. Passino and S. Yurkovich, Fuzzy control: Citeseer, 1998.

[12] D. Driankov, et al., An introduction to fuzzy control: Springer Verlag, 1996.

[13] R. K. Mudi and N. R. Pal, "A self-tuning fuzzy PI controller," Fuzzy sets and systems, vol. 115, pp. 327-338, 2000.

[14] H. X. Li and H. Gatland, "Conventional fuzzy control and its enhancement," Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, vol. 26, pp. 791-797, 1996.

[15] M. Cheng, et al., "New self-tuning fuzzy PI control of a novel doubly salient permanent-magnet motor drive," Industrial Electronics, IEEE Transactions on, vol. 53, pp. 814-821, 2006.

[16] Z. W. Woo, et al., "A PID type fuzzy controller with self-tuning scaling factors," Fuzzy sets and systems, vol. 115, pp. 321-326, 2000.

[17] D. Siljak, "Decentralized control and computations: status and prospects," Annual Reviews in Control, vol. 20, pp. 131-141, 1996.

[18] C. H. Chou and H. C. Lu, "A heuristic self-tuning fuzzy controller," Fuzzy sets and systems, vol. 61, pp. 249-264, 1994.

[19] L. Zheng, "A practical guide to tune of proportional and integral (PI) like fuzzy controllers," 1992, pp. 633-640.

[20] J. Buckley and H. Ying, "Expert fuzzy controller," Fuzzy sets and systems, vol. 44, pp. 373-390, 1991.

[21] C. Batur and V. Kasparian, "Predictive fuzzy expert controllers," Computers & industrial engineering, vol. 20, pp. 199-209, 1991.

[22] P. Xian-Tu, "Generating rules for fuzzy logic controllers by functions," Fuzzy sets and systems, vol. 36, pp. 83-89, 1990.

[23] M. Braae and D. Rutherford, "Selection of parameters for a fuzzy logic controller," Fuzzy sets and systems, vol. 2, pp. 185-199, 1979.

[24] X. G. Duan, et al., "Effective tuning method for fuzzy PID with internal model control," Industrial & Engineering Chemistry Research, vol. 47, pp. 8317-8323, 2008.

[25] M. van de Wal and B. de Jager, "A review of methods for input/output selection," Automatica, vol. 37, pp. 487-510, 2001.

[26] A. Khaki-Sedigh and B. Moaveni, Control configuration selection for multivariable plants vol. 391: Springer Verlag, 2009.

[27] C. PFEIFFER, "On a new measure of interaction for multivariable process control," 1966.

[28] K. H. Johansson, "Relay feedback and multivariable control," PhD thesis, Department of Automatic Control, Lund Institute of Technology, Sweden, 1997.