Pengembangan Blok Fungsi Kendali PI-Fuzi pada IEC 61499

Dirga Eka Putra Lebukan, Awang Noor Indra Wardana, Nazrul Effendy


Automation system in the form of automatic control is needed in one or several operating units in the process industry. Several control system algorithms have been widely implemented in the process industry, one of them is PI (Proportional and Integral) controller. This PI controller has a simple structure, but the adaptive ability of the controller is still not better for the controlled process. Therefore, the development of PI controller is needed to have a better adaptive ability to the process, in order to produce the responses that are also better and more robust. This research develops PI controller by adding the Fuzzy controller algorithm or also known as PI-Fuzzy controller. The PI-Fuzzy controller in this study is applied to the IEC 61499 Programmable Logic Controller (PLC) standard and to see its performance, the PI-Fuzzy controller based on IEC 61499 is tested and validated on an industrial scale process, namely coal mill. The test was carried out for three hours in real-time on the 4DIAC-IDE software, then the response results were compared with the response results of the PI controller. The PI-Fuzzy controller function block based on IEC 61499 made in this study showed good performance in controlling industrial-scale processes. This is demonstrated in testing and validation using a coal mill, with able to achieve the working range of each parameter. The mean value of coal flow parameter is 13.584 kg/s, coal mass accumulation is 2,196 kg, coal output temperature is 83.296 0C, coal moisture is 0.021, and coal fineness is 75.338 %.


automation system; process industry; PI-Fuzzy controller; IEC 61499; coal mill

Full Text:



K. Schwab, “The Fourth Industrial Revolution,” World Economic Forum", pp. 172, 2016.

J. J. Downs and E. F. Vogel, “A Plant Wide Industrial Process Control Problem,” Computers Chem. Eng., vol. 17, 1993.

D. E. Seborg, Process Dynamics and Control, 3rd ed. Hoboken, N.J: John Wiley & Sons, Inc, 2011.

A. N. I. Wardana, “Improved PID Controller with Fuzzy Logic for Grate Coolers in Cement Plants,” ZKG International, vol.56, no.11, pp.82-85, 2004.

D. E. P. Lebukan, A. N. I. Wardana, and N. Effendy, “Implementation of Plant-Wide PI-Fuzzy Controller in Tennessee Eastman Process,” in International Seminar on Application for Technology of Information and Communication (ISemantic), pp. 5, 2019.

R. K. Sahu, S. Panda, and G. T. Chandra Sekhar, “A Novel Hybrid PSO-PS Optimized Fuzzy PI Controller for AGC in Multi Area Interconnected Power Systems,” International Journal of Electrical Power & Energy Systems, vol. 64, pp. 880–893, Jan. 2015.

S. Ozdemir, O. Kaplan, I. Sefa, and N. Altin, “Fuzzy PI controlled Inverter for Grid Interactive Renewable Energy Systems,” IET Renewable Power Generation, vol. 9, no. 7, pp. 729–738, Sep. 2015.

K. Bedoud, M. Ali-rachedi, T. Bahi, and R. Lakel, “Adaptive Fuzzy Gain Scheduling of PI Controller for Control of the Wind Energy Conversion Systems,” Energy Procedia, vol. 74, pp. 211–225, Aug. 2015.

A. M. Ahmed, A. Ali-Eldin, M. S. Elksasy, and F. F. Areed, “Brushless DC Motor Speed Control using both PI Controller and Fuzzy PI Controller,” International Journal of Computer and Application (IJCA), vol. 109, no. 10, pp. 29–35, Jan. 2015.

I. Filip and I. Szeidert, “Adaptive Fuzzy PI Controller with Shifted Control Singletons,” Expert Systems with Applications, vol. 54, pp. 1–12, Jul. 2016.

Z. Tian, S. Li, Y. Wang, and Q. Zhang, “Multi Permanent Magnet Synchronous Motor Synchronization Control based on Variable Universe Fuzzy PI Method,” Engineering Letters, pp. 9, 2015.

V. Kumar, K. P. S. Rana, and P. Mishra, “Robust Speed Control of Hybrid Electric Vehicle using Fractional Order Fuzzy PD and PI Controllers in Cascade Control Loop,” Journal of the Franklin Institute, vol. 353, no. 8, pp. 1713–1741, May 2016.

Lewis and Zoitl, Modelling Control Systems Using IEC 61499. Institution of Engineering and Technology, 2014.

V. Vyatkin, “IEC 61499 as Enabler of Distributed and Intelligent Automation: State-of-the-Art Review,” IEEE Trans. Ind. Inf., vol. 7, no. 4, pp. 768–781, Nov. 2011.

S. Y. Irwan and A. N. I. Wardana, “Distributed Coal Mill Simulator based on IEC 61499,” in The 5th UGM International Conference of Science and Technology, 2019.

K. Ogata, Modern control engineering, 5th ed. Boston: Prentice-Hall, 2010.

J. Guo, G. Wu, and S. Guo, “Fuzzy PID Algorithm-Based Motion Control for the Spherical Amphibious Robot,” in 2015 IEEE International Conference on Mechatronics and Automation (ICMA), Beijing, China, 2015, pp. 1583–1588.

J. Jantzen, Foundations of Fuzzy Control (A Practical Approach), 2nd ed. Wiley, 2013.

V. Agrawal, B. K. Panigrahi, and P. M. V. Subbarao, “A Unified Thermo-Mechanical Model for Coal Mill Operation,” Control Engineering Practice, vol. 44, pp. 157–171, Nov. 2015.

V. Agrawal, B. K. Panigrahi, and P. M. V. Subbarao, “Review of Control and Fault Diagnosis Methods Applied to Coal Mills,” Journal of Process Control, vol. 32, pp. 138–153, Aug. 2015.



  • There are currently no refbacks.