CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Tuning of a PID Controller using Modified Dynamic Group based TLBO Algorithm

by Zhiyong Luo, Qi Guo, Jie Zhao, Shensheng Xu
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 157 - Number 1
Year of Publication: 2017
Authors: Zhiyong Luo, Qi Guo, Jie Zhao, Shensheng Xu
10.5120/ijca2017912593

Zhiyong Luo, Qi Guo, Jie Zhao, Shensheng Xu . Tuning of a PID Controller using Modified Dynamic Group based TLBO Algorithm. International Journal of Computer Applications. 157, 1 ( Jan 2017), 17-23. DOI=10.5120/ijca2017912593

@article{ 10.5120/ijca2017912593,
author = { Zhiyong Luo, Qi Guo, Jie Zhao, Shensheng Xu },
title = { Tuning of a PID Controller using Modified Dynamic Group based TLBO Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 157 },
number = { 1 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 17-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume157/number1/26795-2016912593/ },
doi = { 10.5120/ijca2017912593 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:02:45.757355+05:30
%A Zhiyong Luo
%A Qi Guo
%A Jie Zhao
%A Shensheng Xu
%T Tuning of a PID Controller using Modified Dynamic Group based TLBO Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 157
%N 1
%P 17-23
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a new version of Teaching Learning-Based Optimization (TLBO) algorithm to find the optimal parameters of Proportional Integral Derivative (PID) controller. The proposed algorithm is an altered version of dynamic group strategy TLBO (DGS-TLBO) and is named as modified dynamic group based TLBO (MDG-TLBO) algorithm.  The proposed algorithm is tested on 12 benchmark functions to verify its efficiency over other procedures. The results show that the MDG-TLBO algorithm offers better solution quality and has better convergence rate. Finally, the proposed algorithm is tested on  a three-tank liquid-level control system for the optimization of PID gains.  The simulation result indicate that the proposed algorithm is an effective method in tuning of PID controllers to obtain better performance measures the error values and the time domain specifications.

References
  1. Yaghoobi, S.; Mojallali, H. Tuning of a pid controller using improved chaotic krill herd algorithm. Optik 2016, 127, 4803-4807.
  2. Priyambada, S.; Mohanty, P.K.; Sahu, B.K. In Automatic voltage regulator using tlbo algorithm optimized pid controller, 9th IEEE International Conference on Industrial and Information Systems, ICIIS 2014, December 15, 2014 - December 17, 2014, Gwalior, India, 2015; Institute of Electrical and Electronics Engineers Inc.: Gwalior, India.
  3. Moharam, A.; El-Hosseini, M.A.; Ali, H.A. Design of optimal pid controller using hybrid differential evolution and particle swarm optimization with an aging leader and challengers. Applied Soft Computing 2016, 38, 727-737.
  4. Iruthayarajan, M.W.; Baskar, S. Evolutionary algorithms based design of multivariable pid controller. Expert Systems with Applications 2009, 36, 9159-9167.
  5. Ziegler, J.G.; Nichols, N.B. Optimum settings for automatic controllers. InTech 1995, 42, 94-100.
  6. Cohen, G.; Coon, G. Theoretical consideration of retarded control. Trans. 1953, 75, 827-834.
  7. Jaen-Cuellar, A.Y.; Romero-Troncoso, R.D.J.; Morales-Velazquez, L.; Osornio-Rios, R.A. Pid-controller tuning optimization with genetic algorithms in servo systems. International Journal of Advanced Robotic Systems 2013, 10.
  8. Gaing, Z.-L. A particle swarm optimization approach for optimum design of pid controller in avr system. IEEE Transactions on Energy Conversion 2004, 19, 384-391.
  9. Storn, R.; Price, K. Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization 1997, 11, 341-359.
  10. Hanifah, R.A.; Toha, S.F.; Ahmad, S. In Pid-ant colony optimization (aco) control for electric power assist steering system for electric vehicle, Smart Instrumentation, Measurement and Applications (ICSIMA), 2013 IEEE International Conference on, 25-27 Nov. 2013, 2013; pp 1-5.
  11. Wang, H.; Yuan, X.; Wang, Y.; Yang, Y. Harmony search algorithm-based fuzzy-pid controller for electronic throttle valve. Neural Computing and Applications 2013, 22, 329-336.
  12. Rao, R.V.; Savsani, V.J.; Vakharia, D.P. Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems. Computer-Aided Design 2011, 43, 303-315.
  13. Zou, F.; Wang, L.; Hei, X.H.; Chen, D.B.; Yang, D.D. Teaching-learning-based optimization with dynamic group strategy for global optimization. Information Sciences 2014, 273, 112-131.
  14. Rao, R.V.; Patel, V. An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems. International Journal of Industrial Engineering Computations 2012.
  15. Rao, R.V.; Savsani, V.J.; Vakharia, D.P. Teaching-learning-based optimization: An optimization method for continuous non-linear large scale problems. Information Sciences 2012, 183, 1-15.
  16. Sahu, B.K.; Pati, S.; Mohanty, P.K.; Panda, S. Teaching-learning based optimization algorithm based fuzzy-pid controller for automatic generation control of multi-area power system. Applied Soft Computing 2015, 27, 240-249.
  17. Suresh C Satapathy, A.N. A modified teaching-learning-based optimization (mtlbo) for global search. Recent Patents on Computer Science 2013, 6, 60-72.
  18. V. Rajinikanth, S.C.S. Design of controller for automatic voltage regulator using teaching learning based optimization. Procedia Technology 2015, vol.21, 295-302.
  19. Brest, J.; Greiner, S.; Bokovic, B.; Mernik, M.; Zumer, V. Self-adapting control parameters in differential evolution: A comparative study on numerical benchmark problems. IEEE Transactions on Evolutionary Computation 2006, 10, 646-657.
  20. Qin, A.K.; Huang, V.L.; Suganthan, P.N. Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Transactions on Evolutionary Computation 2009, 13, 398-417.
  21. Kennedy, J.; Mendes, R. In Population structure and particle swarm performance, 2002 Congress on Evolutionary Computation, CEC 2002, May 12, 2002 - May 17, 2002, Honolulu, HI, United states, 2002; IEEE Computer Society: Honolulu, HI, United states, pp 1671-1676.
  22. Peram, T.; Veeramachaneni, K.; Mohan, C.K. In Fitness-distance-ratio based particle swarm optimization, 2003 IEEE Swarm Intelligence Symposium, SIS 2003, April 24, 2003 - April 26, 2003, Indianapolis, IN, United states, 2013; Institute of Electrical and Electronics Engineers Inc.: Indianapolis, IN, United states, pp 174-181.
  23. Mancilla, M.M.A.; Ramirez, Z.S.; Marin, J.A. In Liquid level nonlinear control for a serial coupled tank system, 2014 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2014, November 5, 2014 - November 7, 2014, Ixtapa, Mexico, 2014; Institute of Electrical and Electronics Engineers Inc.: Ixtapa, Mexico.
  24. Cartes, D.; Wu, L. Experimental evaluation of adaptive three-tank level control. ISA Transactions 2005, 44, 283-293.
  25. Singh, S.K.; Katal, N.; Modani, S.G. Multi-objective optimization of pid controller for coupled-tank liquid-level control system using genetic algorithm. In Proceedings of the second international conference on soft computing for problem solving, Babu, B.V.; Nagar, A.; Deep, K.; Pant, M.; Bansal, J.C.; Ray, K.; Gupta, U., Eds. 2014; Vol. 236, pp 59-66.
Index Terms

Computer Science
Information Sciences

Keywords

Teaching-learning-based optimization Liquid-level controller

Powered by PhDFocusTM