DESIGN OF PID CONTROLLER, FLC-SUGENO FOR FAN AND PLATE SYSTEM USING PSO OPTIMIZATION ALGORITHM | Công | TNU Journal of Science and Technology

DESIGN OF PID CONTROLLER, FLC-SUGENO FOR FAN AND PLATE SYSTEM USING PSO OPTIMIZATION ALGORITHM

About this article

Received: 03/10/22                Revised: 31/10/22                Published: 01/11/22

Authors

1. Nguyen Huu Cong Email to author, Thai Nguyen University
2. Nguyen Tien Duy, TNU - University of Technology
3. Le Viet Duc, Thai Nguyen University

Abstract


In this paper, we present the design of PID controllers and fuzzy controllers (Fuzzy Logic Controller - FLC) according to the Sugeno model (FLC) optimal based on the Particle Swarm Optimization algorithm (PSO). The controlling object is the Fan and Plate System (F&P). This is a strong non-linearity object. PID controller is originally designed by Ziegler-Nichols experimental method. The FLC controller is a manual design with membership functions evenly distributed over a defined domain of variables. Next, optimization PSO is used to optimize KP, KI, KD coefficients of the PID controller and optimize the membership function of the FLC. Through simulation showed, the controller after optimizing for the quality of control increased significantly. In particular, the FLC controller produces better control results. Through research, the design of the FLC controller with the PSO optimization algorithm is an effective method.

Keywords


PID Controller; Sugeno Fuzzy Logic Controller; Fuzzy Logic Controller; Fan and Plate System; PSO algorithm

References


[1] S. M. H. Baygi, A. Karsaz, and A. Elahi, “A hybrid optimal PID-Fuzzy control design for seismic exited structural system against earthquake: A salp swarm algorithm,” in 6th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS), 2018, pp. 220-225, doi: 10.1109/CFIS.2018.8336659.

[2] C. Wu, J. Liu, X. Jing, H. Li, and L. Wu, “Adaptive Fuzzy Control for Nonlinear Networked Control Systems,” in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, no. 8, pp. 2420-2430, Aug. 2017, doi: 10.1109/TSMC.2017.2678760.

[3] L. Xing, C. Wen, Z. Liu, H. Su, and J. Cai, “Event-Triggered Adaptive Control for a Class of Uncertain Nonlinear Systems,” in IEEE Transactions on Automatic Control, vol. 62, no. 4, pp. 2071-2076, April 2017, doi: 10.1109/TAC.2016.2594204.

[4] H. Moradi, H. Setayesh, and A. Alasty, “PID-Fuzzy control of air handling units in the presence of uncertainty,” International Journal of Thermal Sciences, vol. 109, pp. 123-135, 2016.

[5] T. Takagi and M. Sugeno, “Fuzzy identification of systems and its applications to modeling and control,” in IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-15, no. 1, pp. 116-132, Jan.-Feb. 1985, doi: 10.1109/TSMC.1985.6313399.

[6] J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proceedings of the 1995 IEEE International Conference on Neural Networks, 4, Perth, WA. Australia, 1995, pp.1942-1948.

[7] I-H. Kuo et al., “An improved method for forecasting enrolments based on fuzzy time series and particle swarm optimization,” Expert systems with applications, vol. 36, pp. 6108-6117, 2009.

[8] H. K. Chiang, R. W. Syu, and W. B. Lin, “The sliding mode controller design of a fan-plate system,” in Proceedings of the 5th intelligent living technology conference, vol. 1, pp. 882-888, 2010.

[9] A. Numsomran and V. Tipsuwanporn, “The design of robust PID control for Fan and Plate process,” in Proceedings of the Ninth IASTED International Conference on Control and Applications, CA, 2007, pp. 273-277.

[10] P. Kungwalrut, M. Thumma, V. Tipsuwanporn, A. Numsomran, and P. Boonsrimuang, “Design MRAC PID control for fan and plate process,” in SICE Annual Conference (SICE), 13-18 Sept. 2011, pp. 2944-2948.

[11] J. B. Ziegler and N. B. Nichols, “Optimum settings for automatic controllers,” ASME Transactions, vol. 64, pp. 759-768, 1942.




DOI: https://doi.org/10.34238/tnu-jst.6580

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