Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm

Cuong Nguyen Cong; Nghia Nguyen Anh; Chuong Trinh Trong; Nghien Nguyen Ba

doi:doi:10.11648/j.ajece.20190301.16

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Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm

Cuong Nguyen Cong, Nghia Nguyen Anh, Chuong Trinh Trong, Nghien Nguyen Ba

Published in American Journal of Electrical and Computer Engineering (Volume 3, Issue 1)

Received: 27 May 2019 Accepted: 20 June 2019 Published: 8 July 2019

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Abstract

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.

Published in	American Journal of Electrical and Computer Engineering (Volume 3, Issue 1)
DOI	10.11648/j.ajece.20190301.16
Page(s)	46-52
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

PI Tuning, CRO Algorithm, Ziegler-Nichols Method, Performance Index, Optimization

References

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[2]	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.
[3]	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).
[4]	Ian Griffin, On-line PID Controller Tuning using Genetic Algorithms, Dublin City University, 2003.
[5]	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.
[6]	Albert Lam, Victor O. K. Li, Chemical Reaction Optimization: A tutorial, Meme tic Computing, March 2012.
[7]	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.
[8]	Brian R Copeland, The Design of PID Controllers using Ziegler Nichols Tuning, March 2008.
[9]	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.
[10]	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.
[11]	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.
[12]	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.
[13]	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.
[14]	Gauri Mantri, N. R. Kulkarni, Design and optimization of PID controller using Genetic Algorithm, International Journal of Research in Engineering and Technology, 2013.
[15]	Shubham Pareek, Meenakshi Kishnani, Rajeev Gupta, Optimal Tuning of PID Controller Using Genetic Algorithm and Swarm Techniques, 2014.

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APA Style

Cuong Nguyen Cong, Nghia Nguyen Anh, Chuong Trinh Trong, Nghien Nguyen Ba. (2019). Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm. American Journal of Electrical and Computer Engineering, 3(1), 46-52. https://doi.org/10.11648/j.ajece.20190301.16

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ACS Style

Cuong Nguyen Cong; Nghia Nguyen Anh; Chuong Trinh Trong; Nghien Nguyen Ba. Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm. Am. J. Electr. Comput. Eng. 2019, 3(1), 46-52. doi: 10.11648/j.ajece.20190301.16

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AMA Style

Cuong Nguyen Cong, Nghia Nguyen Anh, Chuong Trinh Trong, Nghien Nguyen Ba. Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm. Am J Electr Comput Eng. 2019;3(1):46-52. doi: 10.11648/j.ajece.20190301.16

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@article{10.11648/j.ajece.20190301.16,
  author = {Cuong Nguyen Cong and Nghia Nguyen Anh and Chuong Trinh Trong and Nghien Nguyen Ba},
  title = {Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm},
  journal = {American Journal of Electrical and Computer Engineering},
  volume = {3},
  number = {1},
  pages = {46-52},
  doi = {10.11648/j.ajece.20190301.16},
  url = {https://doi.org/10.11648/j.ajece.20190301.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajece.20190301.16},
  abstract = {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.},
 year = {2019}
}

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TY  - JOUR
T1  - Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm
AU  - Cuong Nguyen Cong
AU  - Nghia Nguyen Anh
AU  - Chuong Trinh Trong
AU  - Nghien Nguyen Ba
Y1  - 2019/07/08
PY  - 2019
N1  - https://doi.org/10.11648/j.ajece.20190301.16
DO  - 10.11648/j.ajece.20190301.16
T2  - American Journal of Electrical and Computer Engineering
JF  - American Journal of Electrical and Computer Engineering
JO  - American Journal of Electrical and Computer Engineering
SP  - 46
EP  - 52
PB  - Science Publishing Group
SN  - 2640-0502
UR  - https://doi.org/10.11648/j.ajece.20190301.16
AB  - 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.
VL  - 3
IS  - 1
ER  -

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Author Information

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

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Plain Text BibTeX RIS

APA Style

Cuong Nguyen Cong, Nghia Nguyen Anh, Chuong Trinh Trong, Nghien Nguyen Ba. (2019). Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm. American Journal of Electrical and Computer Engineering, 3(1), 46-52. https://doi.org/10.11648/j.ajece.20190301.16

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ACS Style

Cuong Nguyen Cong; Nghia Nguyen Anh; Chuong Trinh Trong; Nghien Nguyen Ba. Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm. Am. J. Electr. Comput. Eng. 2019, 3(1), 46-52. doi: 10.11648/j.ajece.20190301.16

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AMA Style

Cuong Nguyen Cong, Nghia Nguyen Anh, Chuong Trinh Trong, Nghien Nguyen Ba. Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm. Am J Electr Comput Eng. 2019;3(1):46-52. doi: 10.11648/j.ajece.20190301.16

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@article{10.11648/j.ajece.20190301.16,
  author = {Cuong Nguyen Cong and Nghia Nguyen Anh and Chuong Trinh Trong and Nghien Nguyen Ba},
  title = {Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm},
  journal = {American Journal of Electrical and Computer Engineering},
  volume = {3},
  number = {1},
  pages = {46-52},
  doi = {10.11648/j.ajece.20190301.16},
  url = {https://doi.org/10.11648/j.ajece.20190301.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajece.20190301.16},
  abstract = {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.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Tuning Pi Controller Bases on Chemical Reaction Optimization Algorithm
AU  - Cuong Nguyen Cong
AU  - Nghia Nguyen Anh
AU  - Chuong Trinh Trong
AU  - Nghien Nguyen Ba
Y1  - 2019/07/08
PY  - 2019
N1  - https://doi.org/10.11648/j.ajece.20190301.16
DO  - 10.11648/j.ajece.20190301.16
T2  - American Journal of Electrical and Computer Engineering
JF  - American Journal of Electrical and Computer Engineering
JO  - American Journal of Electrical and Computer Engineering
SP  - 46
EP  - 52
PB  - Science Publishing Group
SN  - 2640-0502
UR  - https://doi.org/10.11648/j.ajece.20190301.16
AB  - 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.
VL  - 3
IS  - 1
ER  -

Copy | Download