Research Article
Self Learning of ANFIS Inverse Control using Iterative Learning Technique
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 21 - Issue 8 |
| Published: May 2011 |
| Authors: Kadhim H. Hassan |
10.5120/2532-3450
|
Kadhim H. Hassan . Self Learning of ANFIS Inverse Control using Iterative Learning Technique. International Journal of Computer Applications. 21, 8 (May 2011), 24-29. DOI=10.5120/2532-3450
@article{ 10.5120/2532-3450,
author = { Kadhim H. Hassan },
title = { Self Learning of ANFIS Inverse Control using Iterative Learning Technique },
journal = { International Journal of Computer Applications },
year = { 2011 },
volume = { 21 },
number = { 8 },
pages = { 24-29 },
doi = { 10.5120/2532-3450 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2011
%A Kadhim H. Hassan
%T Self Learning of ANFIS Inverse Control using Iterative Learning Technique%T
%J International Journal of Computer Applications
%V 21
%N 8
%P 24-29
%R 10.5120/2532-3450
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This paper proposes an approach to tune an Adaptive Neuro Fuzzy Inference System (ANFIS) inverse controller using Iterative Learning Control (ILC). The control scheme consists of an ANFIS inverse model and learning control law. Direct ANFIS inverse controller may not guarantee satisfactory response due to different uncertainties associated with operating conditions and noisy training data. In this paper, the ILC makes a class of self tuning to the inputs of ANFIS inverse controller to minimize the overall system error so that the performance iteratively gets improved. The proposed scheme is simple, effective and lays out a unique tuning procedure for designing ANFIS inverse controller through ILC process.
References
- K. Guney and N. Sankaya ‘’ Adaptive Neural Fuzzy Inference System for Computing the Physical Dimensions of Electrically Thin and Thick Rectangular Microstrip Antennas’’ Int. J. of Infrared and Millimeter Waves Vol.27, No.2, Feb. 2006.
- J.S.R. Jang ‘’ Adaptive Network- Based Fuzzy Inference. System’’ IEEE Trans. On Systems Man. and Cybemetics, Vol.23, No.3, pp 665-685, 1993
- J. D. Wang, N. Y. Chen ’’ Modified ANFIS Inverse Learning for Servo Motor Speed Controller Design’’ Proceedings of CACS Automatic Control Conference Taiwan, Nov. 2005.
- M. A. Denal, F. Palis and A. Zeghbib ‘’ ANFIS Based Modeling and Control of Non-linear systems: A tutorial’’ IEEE International Conference on Systems, Man. and Cybemetics, pp. 3433-3438, 2004
- C. Tao, H. Ruicai and P. Feng ‘’ Adaptive Inverse Control of Linear Motor Based on ANFIS’’ Proceedings of the 29th Chinese Control Conference, China July 2010.
- D. A. Bristow, M. Tharayil and A. G. Alleyne, ‘’A Survey of Iterative Learning Control‘’ IEEE Control Syst. Mag. Vol.26, No.3, pp 96-114, 2006
- H. Sung, Y. Q. Chen and K. Moore “ Iterative Learning Control : Brief Survey and Categorization“ IEEE Transaction on Systems, Man. and Cybernetics-Part C: applications and reviews, Vol. 37, No.6, November 2007.
- K. Assaleh, "Extraction of Fetal Electrocardiogram Using Adaptive Neuro-Fuzzy Inference System" IEEE Transactions on Biomedical Engineering, Vol.54, No.1, PP. 59-68, 2007
- Labview PID and Fuzzy Logic Toolkit User Manual National Instrument, USA June 2009.
Index Terms
Keywords