PID tuning of process plant using particle swarm optimization

Robert Ling Leh Guong; S. Badarol Hisham; I. Elamvazuthi; Sumit Aole; S. Parasuraman; M. K.A.Ahamed Khan

doi:10.1109/ROMA46407.2018.8986712

PID tuning of process plant using particle swarm optimization

Robert Ling Leh Guong
, S. Badarol Hisham
, I. Elamvazuthi
, Sumit Aole
, S. Parasuraman
, M. K.A.Ahamed Khan

Malaysia School of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other

1 Citation (Scopus)

Abstract

PID controller is one of the most robust and well-implemented controller in today's industry. However, the advancement of technology has urged the industry to improve overall process in term of its overshoot, rise time, settling and other domains. In this paper, Particle Swarm Optimization (PSO) algorithm is implemented to optimize the controller parameters in order to improve the system performance of the real pressure plant. Simulation and experimental work are carried out side by side to prove the feasibility of the PSO method. The results show that PSO had successfully improved the system performance of the real pressure plant by 35.44% if compared to Cohen Coon tuning method.

Original language	English
Title of host publication	2018 IEEE 4th International Symposium in Robotics and Manufacturing Automation, ROMA 2018
Publisher	IEEE, Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781728103747
DOIs	https://doi.org/10.1109/ROMA46407.2018.8986712
Publication status	Published - 2018
Event	IEEE International Symposium in Robotics and Manufacturing Automation 2018 - Perambalur, Tamil Nadu, India Duration: 10 Dec 2018 → 12 Dec 2018 Conference number: 4th https://ieeexplore.ieee.org/xpl/conhome/8976031/proceeding (Proceedings)

Conference

Conference	IEEE International Symposium in Robotics and Manufacturing Automation 2018
Abbreviated title	ROMA 2018
Country/Territory	India
City	Perambalur, Tamil Nadu
Period	10/12/18 → 12/12/18
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8976031/proceeding (Proceedings)

Keywords

Coheen Coon
evolutionary algorithm
Particle Swarm Optimization

Access to Document

10.1109/ROMA46407.2018.8986712

Cite this

@inproceedings{9a78ec5423d44b04b22d98aa9fe189f4,

title = "PID tuning of process plant using particle swarm optimization",

abstract = "PID controller is one of the most robust and well-implemented controller in today's industry. However, the advancement of technology has urged the industry to improve overall process in term of its overshoot, rise time, settling and other domains. In this paper, Particle Swarm Optimization (PSO) algorithm is implemented to optimize the controller parameters in order to improve the system performance of the real pressure plant. Simulation and experimental work are carried out side by side to prove the feasibility of the PSO method. The results show that PSO had successfully improved the system performance of the real pressure plant by 35.44\% if compared to Cohen Coon tuning method.",

keywords = "Coheen Coon, evolutionary algorithm, Particle Swarm Optimization",

author = "Guong, \{Robert Ling Leh\} and Hisham, \{S. Badarol\} and I. Elamvazuthi and Sumit Aole and S. Parasuraman and Khan, \{M. K.A.Ahamed\}",

note = "Funding Information: ACKNOWLEDGMENT The sponsor of this project, PETRONAS for providing YUTP Grant, 015LC0-011 is duly acknowledged. The authors would also like to thank Universiti Teknologi PETRONAS, SGGSIE\&T, Monash University Malaysia and UCSI University for supporting this work. Publisher Copyright: {\textcopyright} 2018 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; IEEE International Symposium in Robotics and Manufacturing Automation 2018, ROMA 2018 ; Conference date: 10-12-2018 Through 12-12-2018",

year = "2018",

doi = "10.1109/ROMA46407.2018.8986712",

language = "English",

booktitle = "2018 IEEE 4th International Symposium in Robotics and Manufacturing Automation, ROMA 2018",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

url = "https://ieeexplore.ieee.org/xpl/conhome/8976031/proceeding",

}

Guong, RLL, Hisham, SB, Elamvazuthi, I, Aole, S, Parasuraman, S & Khan, MKAA 2018, PID tuning of process plant using particle swarm optimization. in 2018 IEEE 4th International Symposium in Robotics and Manufacturing Automation, ROMA 2018. IEEE, Institute of Electrical and Electronics Engineers, IEEE International Symposium in Robotics and Manufacturing Automation 2018, Perambalur, Tamil Nadu, India, 10/12/18. https://doi.org/10.1109/ROMA46407.2018.8986712

PID tuning of process plant using particle swarm optimization. / Guong, Robert Ling Leh; Hisham, S. Badarol; Elamvazuthi, I. et al.
2018 IEEE 4th International Symposium in Robotics and Manufacturing Automation, ROMA 2018. IEEE, Institute of Electrical and Electronics Engineers, 2018.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other

TY - GEN

T1 - PID tuning of process plant using particle swarm optimization

AU - Guong, Robert Ling Leh

AU - Hisham, S. Badarol

AU - Elamvazuthi, I.

AU - Aole, Sumit

AU - Parasuraman, S.

AU - Khan, M. K.A.Ahamed

N1 - Conference code: 4th

PY - 2018

Y1 - 2018

N2 - PID controller is one of the most robust and well-implemented controller in today's industry. However, the advancement of technology has urged the industry to improve overall process in term of its overshoot, rise time, settling and other domains. In this paper, Particle Swarm Optimization (PSO) algorithm is implemented to optimize the controller parameters in order to improve the system performance of the real pressure plant. Simulation and experimental work are carried out side by side to prove the feasibility of the PSO method. The results show that PSO had successfully improved the system performance of the real pressure plant by 35.44% if compared to Cohen Coon tuning method.

AB - PID controller is one of the most robust and well-implemented controller in today's industry. However, the advancement of technology has urged the industry to improve overall process in term of its overshoot, rise time, settling and other domains. In this paper, Particle Swarm Optimization (PSO) algorithm is implemented to optimize the controller parameters in order to improve the system performance of the real pressure plant. Simulation and experimental work are carried out side by side to prove the feasibility of the PSO method. The results show that PSO had successfully improved the system performance of the real pressure plant by 35.44% if compared to Cohen Coon tuning method.

KW - Coheen Coon

KW - evolutionary algorithm

KW - Particle Swarm Optimization

UR - https://www.scopus.com/pages/publications/85080063236

U2 - 10.1109/ROMA46407.2018.8986712

DO - 10.1109/ROMA46407.2018.8986712

M3 - Conference Paper

AN - SCOPUS:85080063236

BT - 2018 IEEE 4th International Symposium in Robotics and Manufacturing Automation, ROMA 2018

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - IEEE International Symposium in Robotics and Manufacturing Automation 2018

Y2 - 10 December 2018 through 12 December 2018

ER -

PID tuning of process plant using particle swarm optimization

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Keywords

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