ICA  Vol.4 No.1 , February 2013
Group Method of Data Handling for Modeling Magnetorheological Dampers
ABSTRACT

This paper proposes the use of Group Method of Data Handling (GMDH) technique for modeling Magneto-Rheological (MR) dampers in the context of system identification. GMDH is a multilayer network of quadratic neurons that offers an effective solution to modeling non-linear systems. As such, we propose the use of GMDH to approximate the forward and inverse dynamic behaviors of MR dampers. We also introduce two enhanced GMDH-based solutions. Firstly, a two-tier architecture is proposed whereby an enhanced GMD model is generated by the aid of a feedback scheme. Secondly, stepwise regression is used as a feature selection method prior to GMDH modeling. The proposed enhancements to GMDH are found to offer improved prediction results in terms of reducing the root-mean-squared error by around 40%.


Cite this paper
K. Assaleh, T. Shanableh and Y. Kheil, "Group Method of Data Handling for Modeling Magnetorheological Dampers," Intelligent Control and Automation, Vol. 4 No. 1, 2013, pp. 70-79. doi: 10.4236/ica.2013.41010.
References
[1]   G. P. Liu, “Nonlinear Identification and Control: A Neural Network Approach,” Springer, New York, 2001. doi:10.1007/978-1-4471-0345-5

[2]   P. R. Water, E. J. H. Kerckhoffs and D. Van Welden, “GMDH-Based Dependency Modeling in the Identification of Dynamic Systems,” European Simulation MultiConference (ESM), 2000, pp. 211-218.

[3]   X. Huang, J. Xu and S. Wang “Nonlinear System Identification with Continuous Piecewise Linear Neural Network,” Neurocomputing, Vol. 77, No. 1, 2011, pp. 167-177.

[4]   M. Gonzalez-Olvera and Y. Tang, “A New Recurrent Neurofuzzy Network for Identification of Dynamic Systems,” Fuzzy Sets and Systems, Vol. 158, No. 10, 2007, pp. 1023-1035. doi:10.1016/j.fss.2006.10.002

[5]   G. Wang, “Application of Hybrid Genetic Algorithm to System Identification,” Structural Control and Health Monitoring, Vol. 16, No. 2, 2009, pp. 125-153. doi:10.1002/stc.306

[6]   K. Assaleh, “Extraction of Fetal Electrocardiogram Using Adaptive Neuro-Fuzzy Inference Systems,” IEEE Transactions on Biomedical Engineering, Vol. 54, No. 1, 2007, pp. 59-68. doi:10.1109/TBME.2006.883728

[7]   K. Assaleh and H. Al-Nashash, “A Novel Technique for the Extraction of Fetal ECG Using Polynomial Networks,” IEEE Transactions on Biomedical Engineering, Vol. 52, No. 6, 2005, pp. 1148-1152. doi:10.1109/TBME.2005.844046

[8]   W. Campbell, K. Assaleh and C. Broun, “Speaker Recognition with Polynomial Classifiers,” IEEE Transactions on Speech and Audio Processing, Vol. 10, No. 4, 2002, pp. 205-212. doi:10.1109/TSA.2002.1011533

[9]   A. G. Ivakhnenko, “The Group Method of Data Handling-A Rival of the Method of Stochastic Approximation,” Soviet Automatic Control, Vol. 1, No. 3, 1968, pp. 43-55.

[10]   X.-M. Zhao, Z.-H. Song and P. Li, “A Novel NF-GMDH-IFL and Its Application to Identification and Prediction of Non-Linear Systems,” IEEE Proceedings of the Region 10 Conference on Computers, Communications, Control and Power Engineering, Beijing, 28-31 October 2002, pp. 1286-1289.

[11]   C.-C. Chang and P. Roschke, “Neural Network Modeling of a Magnetorheological Damper,” Journal of Intelligent Material Systems and Structures, Vol. 9, No. 9, 1998, pp. 755-764. doi:10.1177/1045389X9800900908

[12]   M. Askari and A. Davaie-Markazi, “Application of A New Compact Optimized T-S Fuzzy Model to Nonlinear System Identification,” Proceeding of the 5th International Symposium on Mechatronics and Its Applications (ISMA08), Amman, 27-29 May 2008, pp. 1-6.

[13]   M. Duan and J. Shi, “Design for Automobiles MagnetoRheological Damper and Research on Polynomial Model,” International Conference on Electric Information and Control Engineering (ICEICE), Wuhan, 15-17 April 2011, pp. 2085-2088.

[14]   J. Korbicz and M. Mrugalski, “Confidence Estimation of GMDH Neural Networks and Its Application in Fault Detection Systems,” International Journal of Systems Science, Vol. 39, No. 8, 2008, pp. 783-800. doi:10.1080/00207720701847745

[15]   S. Spencer Jr., M. S. Dyke and J. Carlson, “Phenomenological Model of a Magnetorheological Damper,” ASCE Journal of Engineering Mechanics, Vol. 123, No. 3, 1997, pp. 230-238. doi:10.1061/(ASCE)0733-9399(1997)123:3(230)

[16]   K. Assaleh, T. Shanableh and Y. A. Kheil, “System Identification of Magneto-Rheological Damper Using Group Method of Data Handling (GMDH),” 6th International Symposium on Mechatronics and Its Applications, ISMA '09, Sharjah, 23-26 March 2009, pp. 1-6.

[17]   D. Montgomery and G. Runger, “Applied Statistics and Probability for Engineers,” Wiley, Hoboken, 1994.

[18]   T. Shanableh and K. Assaleh, “Feature Modeling Using Polynomial Classifiers and Stepwise Regression,” Neurocomputing, Vol. 73, No. 10-12, 2010, pp. 1752-1759. doi:10.1016/j.neucom.2009.11.045

[19]   V. Atray and P. Roschke, “Design, Fabrication, Testing, and Fuzzy Modeling of a Large Magnetorheological Damper for Vibration Control in a Railcar,” Proceedings of the Joint ASME/IEEE Conference on Railroad Technology, Chicago, 22-24 April 2003, pp. 223-229.

 
 
Top