Call for Paper - September 2020 Edition
IJCA solicits original research papers for the September 2020 Edition. Last date of manuscript submission is August 20, 2020. Read More

Fuzzy Adaptive PID for Flow Control System Based on OPC

Print
PDF
Computational Science - New Dimensions & Perspectives
© 2011 by IJCA Journal
Number 1 - Article 2
Year of Publication: 2011
Authors:
R. Manoj Manjunath
S. Janaki Raman

Manoj R Manjunath and Janaki S Raman. Fuzzy Adaptive PID for Flow Control System based on OPC. IJCA Special Issue on Computational Science - New Dimensions & Perspectives (1):5–8, 2011. Full text available. BibTeX

@article{key:article,
	author = {R. Manoj Manjunath and S. Janaki Raman},
	title = {Fuzzy Adaptive PID for Flow Control System based on OPC},
	journal = {IJCA Special Issue on Computational Science - New Dimensions & Perspectives},
	year = {2011},
	number = {1},
	pages = {5--8},
	note = {Full text available}
}

Abstract

The fuzzy adaptive PID control algorithm based on OPC (Open Process Control) is designed for the flow process station to improve the control performance better than the conventional PID controller. PID controller works well only if the mathematical model of the system could be computed. Hence it is difficult to implement PID control for variable as well as complicated systems. But Fuzzy logic control doesn’t require any precise mathematical model and works good for complex applications also. In this paper, a two input and three output self adapting fuzzy PID controller was designed to control the final control element of the flow process station. S7-300 PLC is connected with the process station. Real time data exchange between the PLC and MATLAB is realized by means of OPC server. Fuzzy logic is developed using fuzzy toolbox available in MATLAB and OPC toolbox helps in fetching data from the OPC server. The proposed method can be used to realize data process and advanced control to improve the quality of the control. New control algorithms created in MATLAB can be checked with real time systems using this method.

Reference

  • OPC Foundation. OPC Data Access Custom Interface Standard Version 2.02[EB/OL]( 2001-12). http://www.opcfoundation.org.
  • Sun Xiang, MATLAB 7.0 Basic Tutorial [M]. Beijing, China, Tsinghua University Press, 2005.
  • The Math Works Inc. OPC Toolbox For Use with MATLAB [P/OL]. 2004-10, http://www.mathworks. com/access / helpdesk/help/pdf_doc/opc/opc.pdf.
  • Vue Wei-jie, Liu Yong-xin (2009), “Boiler Drum Level controlled by Fuzzy Self-adapting PID”, Second Asia-Pacific Conference on Computational Intelligence and Industrial Applications.
  • Zhang Lieping, Zeng Aiqun, Zhang Yunsheng (2007), “On Remote Real-time Communication between MATLAB and PLC Based on OPC Technology”, Proceedings of the 26th Chinese Control Conference.
  • Qingbao Huang,Qianzhong She,Xiaofeng Lin (2010), ” Adaptive Fuzzy PID Temperature Control System Based on OPC and Modbus/TCP Protocol”, 2nd International Asia Conference on Informatics in Control, Automation and Robotics.
  • Qingjin Meng, Baoling Xing, Hongliang Yu, Jingjian Wu (2009), “The Application of Intelligent Control to Combustion Control System of CFB Boiler”, Ninth International Conference on Hybrid Intelligent Systems.