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Reseach Article

Simulation based Modeling and Implementation of Adaptive Control Technique for Non Linear Process Tank

by P. Aravind, M. Valluvan, M. Saranya
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 16
Year of Publication: 2013
Authors: P. Aravind, M. Valluvan, M. Saranya
10.5120/11660-7242

P. Aravind, M. Valluvan, M. Saranya . Simulation based Modeling and Implementation of Adaptive Control Technique for Non Linear Process Tank. International Journal of Computer Applications. 68, 16 ( April 2013), 1-6. DOI=10.5120/11660-7242

@article{ 10.5120/11660-7242,
author = { P. Aravind, M. Valluvan, M. Saranya },
title = { Simulation based Modeling and Implementation of Adaptive Control Technique for Non Linear Process Tank },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 16 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number16/11660-7242/ },
doi = { 10.5120/11660-7242 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:27:59.668312+05:30
%A P. Aravind
%A M. Valluvan
%A M. Saranya
%T Simulation based Modeling and Implementation of Adaptive Control Technique for Non Linear Process Tank
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 16
%P 1-6
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Control of nonlinear process is a complicated task in industrial environment. In this work, adaptive control technique is discussed in control of single conical tank level control system is a nonlinear system is identified mathematically. Analytical modeling were implemented and simulated in MATLAB SIMULINK and transfer function isobtain from the simulated response and PI controller parameter were derived for implementing gain scheduling adaptive controller and synthesis based method is used to obtain PI parameters for multiple linear models. The simulation studies were carried out for two controller parameters. From the results based on Performance indices like Integral Squared Error (ISE), it is proved the controller implemented using gain scheduling adaptive control technique out performs well over synthesis method based tuned multi PI controller.

References
  1. B Ziegler, G. and Nichols, N. B,. Optimum settings for automatic controllers, Trans. ASME, 64, 1942 , PP. 759-768.
  2. Sundaresan K. R, Krishnaswamy R. R, Estimation of time delay, time constant parameters in Time, Frequency and Laplace Domains, Journal of Chemical Engineering. , 56, 257, 1978.
  3. Rahul Shridhar, Douglas J. Cooper," A Novel Tuning For Multivariable MPC,"ISA Transactions,vol - 36,No. 4,PP 273-280.
  4. S. J. Qin and G. Borders, A multi region fuzzy logic controller for nonlinear process control", IEEE Trans. on Fuzzy Systems, 2, 1994 ,PP. 74-81.
  5. Rahul Shridhar , Douglas J. Cooper," A Tuning Strategy for Unconstrained Multivariable MPC," Ind. Eng. Chern. Res. 1998, 37, 4003-4016.
  6. Hirotaka Yoshida, Kenichi Kawata, Yoshikazu Fukuyana, Yosuke Nakanishi, A particle swarm optimization for reactive power and voltage control considering voltage stability, IEEE international conference on intelligent system applications to power systems (ISAP'99), Rio de Janeiro, April 4-8 1999.
  7. Parsopoulos and M. N. Vrahatis, Particle swarm optimizer in noisy and continuously changing environment, Indianapolis, IN, 2001.
  8. Swati Mohanty," Artificial neural network based system Identification and model predictive control of a flotation Column. Journal of Process Control 19 (2009),PP. 991-999.
  9. N. S. Bhuvaneswari , G. Uma , T. R. Rangaswamy," Adaptive and optimal control of a non-linear process using Intelligent controllers," Applied Soft Computing 9, 182-190.
  10. S. Nithya, N. Sivakumaran, T. K. Radhakrishnan and N. Anantharaman" Soft Computing Based Controllers Implementation for Non-linear Process in Real Time" Proceedings of the World Congress on Engineering and Computer Science (WCECS )2010,Vol – 2.
  11. V. R. Ravi, T. Thyagarajan, "Application of Adaptive Control Technique to Interacting Non Linear Systems "Electronics Computer Technology (ICECT), 2011 3rd International Conference on8-10 April 20112 PP: 386 – 392.
  12. V. R. Ravi, T. Thyagarajan, M. Monika Darshini "A Multiple Model Adaptive Control Strategy for Model Predictive controller for Interacting Non Linear Systems "International Conference on Process Automation, Control and Computing (PACC),July 2011. PP:1 – 8.
  13. Sukanya R. Warier, SivanandamVenkatesh "Design of Controllers based on MPC for a Conical Tank System"IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012) March 30, 31, 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Conical Tank Synthesis Method Gain Scheduling MATLAB Non Linear Process