American Journal of Electrical and Computer Engineering
Volume 3, Issue 1, June 2019, Pages: 46-52
Received: May 27, 2019;
Accepted: Jun. 20, 2019;
Published: Jul. 8, 2019
Views 298 Downloads 69
Cuong Nguyen Cong, Department of Electrical Engineering, Hanoi University of Industry, Hanoi, Vietnam
Nghia Nguyen Anh, Department of Electro Mechanics, Hanoi University of Mining and Geology, Hanoi, Vietnam
Chuong Trinh Trong, HaUI Institute of Technology, Hanoi University of Industry, Hanoi, Vietnam
Nghien Nguyen Ba, Department of Information Technology, Hanoi University of Industry, Hanoi, Vietnam
This paper we present Chemical Reaction Optimization (CRO) algorithm for determining optimal parameters of PI controller. The model of doubly fed induction generator (DFIG) is used as a plant in this paper. Tuning PI controller using traditional method such as Ziegler-Nichols (ZN) method usually produces large overshoot and Integral time absolute error, integral absolute error and integral square error performance indices. Therefore, recently researchers have applied random search approach such as genetic algorithm (GA) and particle swarm optimization (PSO) and Grey Wolf Optimizer (GWO) to find optimal parameters for PI controller. Among modern heuristics algorithm, CRO was introduced in 2010, it combines features of both GA and Simulated Annealing (SA) to find global minimum in search space. CRO has been applied to solve successfully many optimization problems such as: Minimum transportation cost, resource-constrained project scheduling problem, channel assignment problem in wireless mesh networks, standard continuous benchmark functions, and so on. In this paper we present to apply CRO algorithm to search optimal parameters for PI controller. The comparison between tuning PI controller by CRO and traditional Ziegler-Nichols method is presented. The simulation results show the advantages of PI tuning using CRO compared to traditional method in terms of performance index and setting time.
Cuong Nguyen Cong,
Nghia Nguyen Anh,
Chuong Trinh Trong,
Nghien Nguyen Ba,
Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm, American Journal of Electrical and Computer Engineering.
Vol. 3, No. 1,
2019, pp. 46-52.
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
M. Araki, PID Control in Control systems, Robotics and Automation, vol II, edited by Heinz Unbehauen, Encyclopedia of Life Support Systems (EOLSS), Developed under the Auspices of the UNESCO, Eolss Publishers, Oxford, UK.
Qiao W, Venayagamoorthy GK, Harley RG (2006), Design of optimal PI controllers for doubly fed induction generators driven by wind turbines using particle swarm optimization. In: IEEE 2006 international joint conference on neural networks (IJCNN ‘06), Georgia Institute of Technology, Atlanta, pp. 1982–1987.
Ioan Constantin Tarca, Komal Khuwaja D/O Shoukat Ali Khuwaja, PID Controller Tuning Optimization with Genetic Algorithms for a Quadcopter, Recent Innovations in Mechatronics (RIiM) Vol. 5. (2018).
Ian Griffin, On-line PID Controller Tuning using Genetic Algorithms, Dublin City University, 2003.
Li Ni, Pen ManMan, Li KenLi, Chemical Reaction Algorithm for Expectation Maximization Clustering, World Academy of Science, Engineering and Technology International Journal of Computer and Information Engineering Vol:10, No:11, 2016.
Albert Lam, Victor O. K. Li, Chemical Reaction Optimization: A tutorial, Meme tic Computing, March 2012.
Allaoua B, Gasbaoui B, Mebarki B, Setting up PID DC Motor speed control alteration parameters using particle swarm optimization strategy, Leonardo Electron J Pract Technol 4:19–32.
Brian R Copeland, The Design of PID Controllers using Ziegler Nichols Tuning, March 2008.
Youcef Bekakra, Djilani ben attous, Optimal tuning of PI controller using PSO optimization for indirect power control for DFIG based wind turbine with MPPT, Int J Syst Assur Eng Manag (July-Sept 2014) 5 (3):219–229.
Prof Dr. Al-Said AbdElAziz Osman, Dr. Amged S. El-Wakeel, Dr. A. kamel, Hatem M. Seoudy, Optimal tuning of PI Controllers for Doubly – Fed Induction Generator-Based Wind Energy Conversion System using Grey Wolf Optimizer, Journal of engineering research and applications, Vol. 5, Issue 11, November 2015, pp. 81-87.
Mahmud Iwan Solihin, Lee Fook Tack, Moey Leap Kean, Tuning of PI controller using Particle Swarm Optimization (PSO), Proceeding of the international conference on advance science, engineering and information technology 2011, Malaysia.
Wei Qiao, Design of optimal PI controllers for Doubly Fed Induction Generators Driven by Wind Turbines using Particle Swarm Optimization, International Joint Conference on Neural Networks, 2006.
Sasmita Behera, Bidyadhar Subydhi, Bibhuti Bhusan Pati, Design of PI controller in Pitch control of Turbine: A comparison of PSO and PS algorithm, International journal of Renewable energy research, 2016.
Gauri Mantri, N. R. Kulkarni, Design and optimization of PID controller using Genetic Algorithm, International Journal of Research in Engineering and Technology, 2013.
Shubham Pareek, Meenakshi Kishnani, Rajeev Gupta, Optimal Tuning of PID Controller Using Genetic Algorithm and Swarm Techniques, 2014.