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

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Zhiyong Luo, Qi Guo, Jie Zhao, Shensheng Xu

Zhiyong Luo, Qi Guo, Jie Zhao and Shensheng Xu. Tuning of a PID Controller using Modified Dynamic Group based TLBO Algorithm. International Journal of Computer Applications 157(1):17-23, January 2017. BibTeX

	author = {Zhiyong Luo and Qi Guo and Jie Zhao and Shensheng Xu},
	title = {Tuning of a PID Controller using Modified Dynamic Group based TLBO Algorithm},
	journal = {International Journal of Computer Applications},
	issue_date = {January 2017},
	volume = {157},
	number = {1},
	month = {Jan},
	year = {2017},
	issn = {0975-8887},
	pages = {17-23},
	numpages = {7},
	url = {http://www.ijcaonline.org/archives/volume157/number1/26795-2016912593},
	doi = {10.5120/ijca2017912593},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


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.


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Teaching-learning-based optimization, Liquid-level controller