WSEAS Transactions on Systems and Control


Print ISSN: 1991-8763
E-ISSN: 2224-2856

Volume 14, 2019

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.


Volume 14, 2019



Obtaining Optimal PIDA Controller for Temperature Control of Electric Furnace System via Flower Pollination Algorithm

AUTHORS: Noppadol Pringsakul, Deacha Puangdownreong, Chaiyo Thammarat, Sarot Hlangnamthip

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ABSTRACT: The electric furnace temperature control system is one of the real-world second-order systems plus time delay (SOSPD) widely used as the process control in industries. It is normally operated under the PID feedback control loop. The PIDA controller, however, performed better response than the PID controller for higher order plant. In this paper, an optimal PIDA controller design for the electric furnace temperature control system is presented. Regarding to modern optimization context, the flower pollination algorithm (FPA) which is one of the most efficient population-based metaheuristic optimization techniques is applied to search for the appropriate PIDA’s parameters. The proposed FPA-based PIDA design framework is considered as the constrained optimization problem. System responses obtained by the PIDA controller designed by the FPA will be compared with those obtained by the PID controller also designed by the FPA. As results, it was found that the PIDA can provides the very satisfactory tracking and regulating responses of the electric furnace temperature control system superior to the PID, significantly.

KEYWORDS: PIDA Controller, Electric Furnace Temperature Control, Metaheuristic Optimization

REFERENCES:

[1] A. Dwyer, Handbook of PI and PID Controller Tuning Rules, Imperial College, 2009.

[2] B. G. Liptak, Instrumentation Engineer’s Handbook’ Process Control, CRC Press, 1995.

[3] Y. Han, J. Jinling, C. Guangjian and C. Xizhen, Temperature Control of Electric Furnace based on Fuzzy PID, IEEE Trans. ICEOE, 2011, pp. V3-41-V3-44.

[4] F. Teng and H. Li, Adaptive Fuzzy Control for the Electric Furnace, IEEE Trans. ICIS, 2009, pp. 439-443.

[5] X. Junming, Z. Haiming, J. Lingyun and Z. Rui, Based on Fuzzy–PID Self-Tuning Temperature Control System of the Furnace, IEEE Trans. ICEICE, 2011, pp. 15-17.

[6] W. Ding-du, 2010. Decoupling Control of Electric Heating Furnace Temperature Based on DRNN Neural Network, IEEE Trans. ICECT, 2010, pp. 261-264. Fig. 6 Convergent rates over 50 trials. Fig. 7 Step-input (tracking) responses of the electric furnace temperature control system. Fig. 8 Step-disturbance (regulating) responses of the electric furnace temperature control system.

[7] V. Sinlapakun and W. Assawinchaichote, PID Controller Based Nelder Mead Algorithm for Electric Furnace System with Disturbance, ECTI Trans. Computer and Information Technology, Vol. 10, No. 1, 2016, pp. 71-79.

[8] B. Srilakshmi and K. Venkataratnam, Temperature Control of Electric Furnace using Genetic Algorithm Based PID Controller, International Journal of Advanced Engineering and Global Technology, Vol. 3, No. 11, 2015, pp. 1348-1352.

[9] D. Sain, S. K. Swain, S. K. Mishra and S. Dutta, Robust Set-Point Weighted PID Controller Design Using Genetic Algorithm for Electric Furnace Temperature Control System, International Journal of Control Theory and Applications, Vol. 9, No. 39, 2016, pp. 29-36.

[10] S. Hlungnamthip, N. Pringsakul, A. Nawikavatan and D. Puangdownreong, FPA-Based PID Controller Design for Temperature Control of Electric Furnace System, The 2018 International Conference on Engineering and Natural Science (ICENS 2018), 2018, pp. 60- 68.

[11] S. Jung and R. C. Dorf, Analytic PIDA Controller Design Technique for a Third Order System, Proceedings of the 35th IEEE Conference on Decision and Control, Kobe, 1996, pp. 2513-2518.

[12] S. Sornmuang and S. Sujitjorn, GA-Based PIDA Control Design Optimization with an Application to AC Motor Speed Control, International Journal of Mathematics and Computers in Simulation, Vol. 4, No. 3, 2010, pp. 67-80.

[13] D. Puangdownreong and S. Suwannarongsri, Torsional Resonance Suppression via PIDA Controller Designed by the Particle Swarm Optimization, The ECTI–CON International Conference, 2008, pp. 673-676.

[14] C. Thammarat, P. Sukseam, D. Puangdownreong and S. Suwannarongsri, Design of PIDA Controllers via Particle Swarm Optimization, The ANSCSE 2008 Symposium, 2008, pp. 393- 398.

[15] D. Puangdownreong, Application of Current Search to Optimum PIDA Controller Design, Intelligent Control and Automation, Vol .3, No.4, 2012, pp. 303-312.

[16] D. Puangdownreong, S. Sumpunsri, M. Sukchum, C. Thammarat, S. Hlangnamthip and A. Nawikavatan, FA-Based Optimal PIDA Controller Design for AVR System, The iEECON2018 International Conference, 2018, pp. 548-551.

[17] C. Thammarat, K. Lurang, D. Puangdownreong, S. Suwammarongsri, S. Hlangnamthip and A. Nawikavatan, Application of BatInspired Algorithm to Optimal PIDA Controller Design for Liquid-Level System, The iEECON2018 International Conference, 2018, pp. 556-559.

[18] A. Nawikavatan, T. Jitwang, C. Thammarat and D. Puangdownreong, Application of Cuckoo Search to Optimal PIDA Controller Design for Three-Tank Liquid-Level Control System, The 2018 International Conference on Engineering and Natural Science (ICENS 2018), 2018, pp. 51-59.

[19] X. S. Yang, Flower Pollination Algorithm for Global Optimization, Unconventional Computation and Natural Computation, Lecture Notes in Computer Science, Vol. 7445, 2012, pp. 240-249.

[20] X. S. Yang, M. Karamanoglua and X. He, Multi-Objective Flower Pollination Algorithm for Optimization, Procedia Computer Science, Vol. 18, 2013, pp. 861-868.

[21] S. Suwannarongsri and D. Puangdownreong, Application of Flower Pollination Algorithm for Solving Medium Scaled Traveling Transportation Problems, The 2018 International Conference on Engineering and Natural Science (ICENS 2018), 2018, pp. 34- 42.

[22] D. Puangdownreong, Optimal State-Feedback Design for Inverted Pendulum System by Flower Pollination Algorithm, International Review of Automatic Control (IREACO), Vol. 9, No. 5, 2016, pp. 289-297.

[23] C. Thammarat, A. Nawikavatan and D. Puangdownreong, Application of Flower Pollination Algorithm to PID Controller Design for Three-Tank Liquid-Level Control System, The 9th International Conference on Sciences, Technology and Innovation for Sustainable Well-Being (STIWB), 2017, pp. 42-46.

[24] S. Hlungnamtip, C. Thammarat and D. Puangdownreong, Obtaining Optimal PID Controller for DC Motor Speed Control System via Flower Pollination Algorithm, The 9th International Conference on Sciences, Technology and Innovation for Sustainable Well-Being (STIWB), 2017, pp. 52-56.

[25] D. Puangdownreong, C. Thammarat, S. Hlungnamtip and A. Nawikavatan, Application of Flower Pollination Algorithm to Parameter Identification of DC Motor Model, The 2017 International Electrical Engineering Congress (iEECON–2017), Vol. 2, 2017, pp. 711-714.

[26] J. Paulusov and M. Dbravsk, Application of Design of PID Controller for Continuous Systems, FEI STU, Slovak Republic, 2012.

[27] B. J. Glover, Understanding Flowers and Flowering: An Integrated Approach, Oxford University Press, 2007.

[28] P. Willmer, Pollination and Floral Ecology, Princeton University Press, 2011.

[29] K. Balasubramani and K. Marcus, A Study on Flower Pollination Algorithm and Its Applications, International Journal of Application or Innovation in Engineering & Management (IJAIEM), Vol. 3, 2014, pp. 320- 325.

[30] I. Pavlyukevich, Lévy Flights, Non-Local Search and Simulated Annealing, Journal of Computational Physics, Vol. 226, 2007, pp. 1830-1844.

WSEAS Transactions on Systems and Control, ISSN / E-ISSN: 1991-8763 / 2224-2856, Volume 14, 2019, Art. #1, pp. 1-7


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