A New Method of Optimum Tuning for Cascade Control Systems

Received: 13-11-2015

Accepted: 08-03-2016

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KỸ THUẬT VÀ CÔNG NGHỆ

How to Cite:

Hien, N., & Dat, N. (2024). A New Method of Optimum Tuning for Cascade Control Systems. Vietnam Journal of Agricultural Sciences, 14(3), 469–476. http://testtapchi.vnua.edu.vn/index.php/vjasvn/article/view/1414

A New Method of Optimum Tuning for Cascade Control Systems

Nguyen Thi Hien (*) 1 , Nguyen Van Dat 1

  • 1 Khoa Cơ - Điện, Học viện Nông nghiệp Việt Nam
  • Keywords

    Cascade control, data - driven approach, FRIT, optimal controller

    Abstract


    Cascade control systems are widely used in practice with one or more loops inside the primary loop and thecontrollers are in cascade. In this structure, the control signal calculated by the outer loop is the setpoint of the inner loop. This paper presents an algorithm that directly uses the experimental data to simultaneously tune parameters of the controllers in cascade control systems. The algorithm does not require a mathematical model of the plan but only one-shot experimental data collected from the closed loop system.

    References

    Campi M. C., A. Lecchini, and S. M. Savaresi (2002). Virtual reference feedback tuning: A direct method for design of feedback controllers. Automatica, 38(8): 1337-1346.

    Kaneko O., S. Souma, T. Fujii (2005). A fictitious reference iterative tuning (FRIT) in the two-degree of freedom control scheme and its application to closed loop system identification. Proceedings of the 16th IFAC World Congress, pp. 104-109.

    Nguyen Thi Hien (2013). Studies on data - driven approach in internal model control, PhD. dissertation, Kanazawa University, Japan.

    Hjalmarsson H., M. Gevers, S. Gunnarsson, and O. Lequin (1998). Iterative feedback tuning: Theory and application. IEEE Control Systems Magazine, 18(4): 26-41.

    Lee Y., Park S. and Lee M. (1998). PID controller tuning to obtain desired closed loop responses for cascade control systems. Industrial & Engineering Chemistry Research, 37(5): 1859-1865.

    Marlin T. E. (2000). Process control. McGraw-Hill, 2nd Edition, ISBN: 0070393621.

    Safonov M. G. and T. C. Tsao (1997). The unfalsified control concept and learning. IEEE Transaction on Automatic Control, 42(6): 843-847.

    Souma S., O. Kaneko and T. Fujii (2004). A new method of controller parameter tuning based on input-output data - fictitious reference iterative tuning (FRIT). Proceedings of the 8th IFAC Workshop on Adaptation and Learning Control and Signal Processing (ALCOSP 04), pp. 788-794.