Experimental evaluation of optimal tuning for PID parameters in an AVR system

Document Type : Article

Authors

1 Railway Engineering Department, Iran University of Science and Technology (IUST), Tehran, Iran

2 Department of Electrical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran

Abstract

Automatic Voltage Regulator (AVR) is employed to stabilize the output voltage of the generators in the electric power plants. However, reliable performance of AVR depends on professional tuning of its PID controller’s parameters. Therefore, different optimization algorithms are used to determine those parameters. The objective of the optimization is defined as minimizing the characteristics of transient step response such as settling time, rise time, overshoot, and steady state error. Then, to verify the optimization results, a simulator is built experimentally for AVR and PID system that can also be used for other studies on AVR systems. The experimental results are compared with those of MATLAB and Pspice Software. Close agreement between the simulation and experimental results confirms the success of the optimization.

Keywords


References:
1. Batmani, Y. and Golpira, H. "Automatic voltage regulator design using a modified adaptive optimal approach", Int. J. Electr. Power Energy Syst., 104, pp. 349-357 (2019).
2. Ekinci, S. and Hekimoglu, B. "Improved kidneyinspired algorithm approach for tuning of PID controller in AVR system", IEEE Access, 7, pp. 39935- 39947 (2019).
3. Zigeler, J.G. and Nichols, N.B. "Optimization setting for automatic controller", Trans. ASME., 64(11), pp. 759-769 (1942).
4. Nouman, K., Asim, Z., and Qasim, K. "Comprehensive study on performance of PID controller and its applications", 2nd IEEE Adv. Inf. Manag. Autom. Control Conf., IEEE., pp. 1574-1579 (2018).
5. George, R.G., Hasanien, H.M., Badr, M.A., et al. "A comparative study among different algorithms investigating optimum design of PID controller in automatic voltage regulator", 53rd Int. Univ. Power Eng. Conf., IEEE., pp. 1-6 (2018).
6. Mukherjee, V. and Ghoshal, S.P. "Comparison of intelligent fuzzy based AGC coordinated PID controlled and PSS controlled AVR system", Int. J. Electr. Power Energy Syst., 29(9), pp. 679-689 (2007).
7. Mukherjee, V. and Ghoshal, S.P. "Intelligent particle swarm optimized fuzzy PID controller for AVR system", Electr. Power Syst. Res., 77(12), pp. 1689-1698 (2007).
8. Bhutto, A.A., Chachar, F.A., Hussain, M., Bhutto, D.K., and Bakhsh, S.E., "Implementation of probabilistic neural network (PNN) based automatic voltage regulature (AVR) for excitation control system in Matlab", 2nd Int. Conf. Comput. Math. Eng. Technol., IEEE., pp. 1-5 (2019).
9. Lennartson, B. and Kristiansson, B. "Evaluation and tuning of robust PID controllers", IET Control Theory Appl., 3(3), pp. 294-302 (2009).
10. Mohammed, N.F., Song, E., Ma, X., et al. "Tuning of PID controller of synchronous generators using genetic algorithm", IEEE Int. Conf. Mechatronics Autom., IEEE., pp. 1544-1548 (2014).
11. Rahimian, M. and Raahemifar, K. "Optimal PID controller design for AVR system using particle swarm optimization algorithm", Electr. Comput. Eng. (CCECE), 24th Can. Conf., IEEE., pp. 337-340 (2011).
12. Krohling, R.A. and Rey, J.P. "Design of optimal disturbance rejection PID controllers using genetic algorithms", IEEE Trans. Evol. Comput., 5(1), pp. 78- 82 (2001).
13. Fogel, D.B., Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, John Wiley & Sons (2006).
14. Jittapramualboon, S. and Assawinchaichote, W. "Optimization of PID controller based on Taguchi combined particle swarm optimization for AVR system of synchronous generator", 2016 Int. Comput. Sci. Eng. Conf., IEEE, pp. 1-6 (2016).
15. Nangru, D., Bairwa, D.K., Singh, K., et al. "Modified PSO based PID controller for stable processes", Int. Conf. Control. Autom. Robot. Embed. Syst., IEEE., pp. 1-5 (2013).
16. Yegireddy, N.K. and Panda, S. "Design and performance analysis of PID controller for an AVR system using multi-objective non-dominated shorting genetic algorithm-II", Int. Conf. Smart Electr. Grid, IEEE., pp. 1-7 (2014).
17. Pan, I. and Das, S. "Chaotic multi-objective optimization based design of fractional order PID controller in AVR system", Int. J. Electr. Power Energy Syst., 43(1), pp. 393-407 (2012).
18. Chatterjee, A., Mukherjee, V., and Ghoshal, S.P., "Velocity relaxed and craziness-based swarm optimized intelligent PID and PSS controlled AVR system", Int. J. Electr. Power Energy Syst., 31(7-8), pp. 323-333 (2009).
19. Hasanien, H.M. "Design optimization of PID controller in automatic voltage regulator system using Taguchi combined genetic algorithm method", IEEE Syst. J., 7(4), pp. 825-831 (2013).
20. Gozde, H., Taplamacioglu, M.C., and Ari, M. "Automatic Voltage Regulator (AVR) design with chaotic particle swarm optimization", Proc. 2014 6th Int. Conf. Electron. Comput. Artif. Intell., IEEE., pp. 23- 26 (2014).
21. Blondin, M.J., Sanchis, J., Sicard, P., et al. "New optimal controller tuning method for an AVR system using a simplified ant colony optimization with a new constrained Nelder-mead algorithm", Appl. Soft Comput., 62, pp. 216-229 (2018).
22. Panda, S., Sahu, B.K., and Mohanty, P.K. "Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization", J. Franklin Inst., 349(8), pp. 2609-2625 (2012).
23. Femmy Nirmal, J. and Jeraldin Auxillia, D. "Adaptive PSO based tuning of PID controller for an automatic voltage regulator system", Int. Conf. Circuits, Power Comput. Technol., IEEE., pp. 661-666 (2013).
24. Sambariya, D.K. and Gupta, T., "Optimal design of PID controller for an AVR system using monarch butter y optimization", Int. Conf. Information, Commun. Instrum. Control, IEEE., pp. 1-6 (2017).
25. Sonawane, P., Savakhande, V.B., Chewale, M.A., et al. "Optimization of PID controller for automatic voltage regulator system using Taguchi method", Int. Conf. Comput. Commun. Informatics, IEEE., pp. 1-6 (2018).
26. Ekinci, S., Hekimoglu, B., and Kaya, S. "Tuning of PID controller for AVR system using salp swarm algorithm", Int. Conf. Artif. Intell. Data Process., IEEE., pp. 1-6 (2018).
27. Gozde, H. and Taplamacioglu, M.C. "Comparative performance analysis of artificial bee colony algorithm for automatic voltage regulator (AVR) system", J. Franklin Inst., 348(8), pp. 1927-1946 (2011).
28. Manuaba, I., Abdillah, M., Soeprijanto, A., et al.  Coordination of PID based power system stabilizer and AVR using combination bacterial foraging technique — Particle swarm optimization", Fourth Int. Conf. Model. Simul. Appl. Optim., IEEE., pp. 1-7 (2011).
29. Mandal, A., Zafar, H., Ghosh, P., et al. "An efficient memetic algorithm for parameter tuning of PID controller in AVR system", 11th Int. Conf. Hybrid Intell. Syst., IEEE., pp. 265-270 (2011).
30. Nayak, N., Routray, S.K., and Pradhan, S. "Optimal design of PID controller for AVR in a multi machine power system using modified PSO and fire  y optimization technique", IEEE Power, Commun. Inf. Technol. Conf., IEEE., pp. 768-775 (2015).
31. Madinehi, N., Shaloudegi, K., Abedi, M., et al. "Optimum design of PID controller in AVR system using intelligent methods", 2011 IEEE Trondheim PowerTech, IEEE., pp. 1-6 (2011).
32. Hashemi, F. and Mohammadi, M. "Combination of continuous action reinforcement learning automata & PSO to design a PID controller for AVR system", Int. J. Eng., 28(1(A)) (2015).
33. Puralachetty, M.M., Pamula, V.K., and Akula, V.N.B. "Comparison of different optimization algorithms with two stage initialization for PID controller tuning in automatic voltage regulator system", IEEE Students' Technol. Symp., IEEE., pp. 152-156 (2016).
34. Chatterjee, S. and Mukherjee, V. "PID controller for automatic voltage regulator using teaching-learning based optimization technique", Int. J. Electr. Power Energy Syst., 77, pp. 418-429 (2016).
35. Sahu, B.K., Panda, S., Mohanty, P.K., et al. "Robust analysis and design of PID controlled AVR system using pattern search algorithm", 2012 IEEE Int. Conf. Power Electron. Drives Energy Syst. IEEE, pp. 1-6 (2012).
36. Lahcene, R., Abdeldjalil, S., and Aissa, K. "Optimal tuning of fractional order PID controller for AVR system using simulated annealing optimization algorithm", 5th Int. Conf. Electr. Eng.-Boumerdes, IEEE., pp. 1-6 (2017).
37. Armeev, D.V., Chekhonadskikh, A.V., and Voevoda, A.A. "Modal optimization of AVR for synchronous generator using the finite gradient", Int. Sib. Conf. Control Commun., IEEE., pp. 1-4 (2015).
38. Gozde, H., Taplamacioglu, M.C., and Ari, M. "Simulation study for global neighborhood algorithm based optimal automatic voltage regulator (AVR) system", 5th Int. Istanbul Smart Grid Cities Congr. Fair, IEEE., pp. 46-50 (2017).
39. Dadvandipour, S., Khalili Dizaji, N., and Rosshan Entezar, S. "An approach to optimize the proportionalintegral- derivative controller system", Proc. 2015 16th Int. Carpathian Control Conf., IEEE., pp. 95-99 (2015).
40. Kumar, A. and Shankar, G. "Priority based optimization of PID controller for automatic voltage regulator system using gravitational search algorithm", Int. Conf. Recent Dev. Control. Autom. Power Eng., IEEE., pp. 292-297 (2015).
41. Afroomand, A., Tavakoli, S., and Tavakoli, M. "An efficient metaheuristic optimization approach to the problem of PID tuning for automatic voltage regulator systems", IEEE Int. Conf. Adv. Intell. Mechatronics, IEEE., pp. 1682-1687 (2016).
42. Menhas, M.I., Wang, L., Ayesha, N.-A., et al. "Continuous human learning optimizer based PID controller design of an automatic voltage regulator system", Aust. New Zeal. Control Conf., IEEE., pp. 148-153 (2018).
43. Demiroren, A., Hekimoglu, B., Ekinci, S., et al. "Artificial electric field algorithm for determining controller parameters in AVR system", Int. Artif. Intell. Data Process. Symp., IEEE., pp. 1-7 (2019).
44. Mosaad, A.M., Attia, M.A., and Abdelaziz, A.Y. "Whale optimization algorithm to tune PID and PIDA controllers on AVR system", Ain Shams Eng. J., 10(4), pp. 755-767 (2019).
45. Bingul, Z. and Karahan, O. "A novel performance criterion approach to optimum design of PID controller using cuckoo search algorithm for AVR system", J. Franklin Inst., 355(13), pp. 5534-5559 (2018).
46. Sikander, A. and Thakur, P. "A new control design strategy for automatic voltage regulator in power system", ISA Trans., 100, pp. 235-243 (2020).
47. Zhu, H., Li, L., Zhao, Y., et al. "CAS algorithm-based optimum design of PID controller in AVR system", Chaos, Solitons & Fractals, 42(2), pp. 792-800 (2009).
48. Dos Santos Coelho, L. "Tuning of PID controller for an automatic regulator voltage system using chaotic optimization approach", Chaos, Solitons & Fractals, 39(4), pp. 1504-1514 (2009).
49. Verma, S.K., Yadav, S., and Nagar, S.K. "Controlling of an automatic voltage regulator using optimum integer and fractional order PID controller", IEEE Work. Comput. Intell. Theor. Appl. Futur. Dir., IEEE., pp. 1-5 (2015).
50. Gaing, Z. "A particle swarm optimization approach for optimum design of PID controller in AVR system", IEEE Transactions on Energy Conversion, 19(2), pp. 384-391 (2004).
51. Mirjalili, S. and Lewis, A. "The whale optimization algorithm", Adv. Eng. Softw., 95, pp. 51-67 (2016).
52. Mirjalili, S. "The ant lion optimizer", Adv. Eng. Softw., 83, pp. 80-98 (2015).
53. Faris, H., Mirjalili, S., Aljarah, I., et al. "Salp swarm algorithm: theory, literature review, and application in extreme learning machines", Nature-Inspired Optimizers, Springer, 811, pp. 185-199 (2020).
54. Mirjalili, S., Gandomi, A.H., Mirjalili, S.Z., et al. "Salp swarm algorithm: A bio-inspired optimizer for engineering design problems", Adv. Eng. Softw., 114, pp. 163-191 (2017).
55. Mirjalili, S. "Dragon y algorithm: a new metaheuristic optimization technique for solving singleobjective, discrete, and multi-objective problems", Neural Comput. Appl., 27(4), pp. 1053-1073 (2016).
56. Holland, J.H., Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, University of Michigan Press (1975).
57. Kennedy, J. and Eberhart, R. "Particle swarm optimization", Proceedings of ICNN'95 - International Conference on Neural Networks, 4, pp. 1942-1948 (1995). Doi: 10.1109/ICNN.1995.488968.
58. Karaboga, D. "An Idea Based on Honey Bee Swarm for Numerical Optimization", Technical Report-tr06, Erciyes university, engineering faculty, computer engineering department (2005).