CFP last date
20 June 2024
Call for Paper
July Edition
IJCA solicits high quality original research papers for the upcoming July edition of the journal. The last date of research paper submission is 20 June 2024

Submit your paper
Know more
Reseach Article

Implementation of Neural Network for PID Controller

Published on June 2015 by Ashlesha Panbude, Manish Sharma
National Conference on Emerging Trends in Advanced Communication Technologies
Foundation of Computer Science USA
NCETACT2015 - Number 2
June 2015
Authors: Ashlesha Panbude, Manish Sharma
5fbb0b41-f016-4679-8e11-39d47053867e

Ashlesha Panbude, Manish Sharma . Implementation of Neural Network for PID Controller. National Conference on Emerging Trends in Advanced Communication Technologies. NCETACT2015, 2 (June 2015), 31-34.

@article{
author = { Ashlesha Panbude, Manish Sharma },
title = { Implementation of Neural Network for PID Controller },
journal = { National Conference on Emerging Trends in Advanced Communication Technologies },
issue_date = { June 2015 },
volume = { NCETACT2015 },
number = { 2 },
month = { June },
year = { 2015 },
issn = 0975-8887,
pages = { 31-34 },
numpages = 4,
url = { /proceedings/ncetact2015/number2/20990-2026/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Emerging Trends in Advanced Communication Technologies
%A Ashlesha Panbude
%A Manish Sharma
%T Implementation of Neural Network for PID Controller
%J National Conference on Emerging Trends in Advanced Communication Technologies
%@ 0975-8887
%V NCETACT2015
%N 2
%P 31-34
%D 2015
%I International Journal of Computer Applications
Abstract

The conventional PID (proportional-integral derivative) controller is widely applied to industrial automation and process control field because of its simple structure and robustness, but it does not work well for nonlinear system, time-delayed linear system and time varying system. Artificial Neural Network (ANN) can solve great variety of problems in areas of control systems, pattern recognition, image processing and medical diagnostic. A Neural Network is a powerful data-modeling tool that is able to capture and represent complex input/output relationships. This paper represents the advantage of using neural network for PID controller. PID controller for surge tank has been implemented in MATLAB.

References
  1. Yu Yong quan, Huang Ying and Zeng Bi, "A PID Neural Network Controller," Proceeding of the International Joint Conference on Neural Net Works, IEEE Computer Society Press, California, vol. 3, pp. 1933-1938, 2003.
  2. Indranil Pan, Saptarshi Das, Amitava Gupta, "Tuning of an optimal fuzzy PID controller with stochastic algorithms for network control systems with random time delay," ISA Transaction, vol. 50, pp. 28-36, 2011.
  3. G. jahedi, M. M. Ardehali, "Genetic algorithm-based fuzzy- PID control methodologies for enhancement of energy efficiency of a dynamic energy system," Energy Conversion and management, vol. 52, pp. 725-732, 2011.
  4. Saptarshi Das, Indranil Pan, Shantanu Das, "A novel fractional order fuzzy PID controller and its optimal time domain tuning based on integral performance indices," Engineering Applications of Aritficial Intelligence, online, 2010.
  5. Yaohua Guo, Junshuang ma, Minglin Yao, "The neural network PID controller for cement Rotary kiln Temperature based on FPGA", Information science and engineering(ISISE) December 2010.
  6. Liguo Qu, Yourui Huang and Liuyi Ling, "Design if Intelligent PID controller based on Adaptive Genetic Algorithm and Implementation of FPGA", Springer 2008.
  7. Wei-Der Chang. , "A multi-crossover genetic approach to multivariable PID controllers" Tuning [J]. Expert Systems with Applications, 2007, 33(3): 620-626.
  8. Shu Huailin, "PID Neural Network Control for Complex Systems," Processing's of International Conference on Computational Intelligence for Modelling, Control and Automation CCIMCA 99'2,10s Press, 1999, pp. 166-171.
  9. Moradi, M. H. "New Techniques for PID Controller Design," Proceeding of 2003 IEEE Conference on Control Applications, IEEE Press, New York, vol. 2, pp. 903-908, 2003.
  10. Sangeetha T, Meenal C, "Digital Implementation of Artificial Neural Network for Function Approximation and Pressure Control Applications," IOSR Journal of Electronics and Communication Engineering (IOSR-JECE), Volume 5, Issue 5, PP 34-39 (Mar. - Apr. 2013).
  11. Liu Luoren, Luo Jinling "Research of PID Control Algorithm Based on Neural Network", science direct-2011.
Index Terms

Computer Science
Information Sciences

Keywords

Pid Controller Artificial Neural Network.