A SUPPORT VECTOR REGRESSION METHOD FOR REDUCING THE HIGH-ORDER SYSTEMS TO FIRST-ORDER PLUS TIME-DELAY FORMS

[1] J.P., Richard, “Time Delay Systems: An Overview of
Some Recent Advances and Open Problems”,
Automatica, Vol: 39, Issue: 10, pp. 1667-1694, 2003.
[2] S.V., Drakunov, W., Perruquetti, J.P., Richard, “Delay
Identification in Time-Delay Systems Using Variable
Structure Observers”, Annual Reviews in Control, Vol:
30, Issue: 2, pp. 143-158, 2006.
[3] V., Venkatashankar, M., Chidambaram, “Design of P and
PI Controllers for Unstable 1st Order Plus Time-Delay
Systems”, International Journal of Control, Vol: 60,
No:1, pp.137-144, 1994.
[4] S., Tavakoli, M., Tavakoli, “Optimal Tuning of PID
Controllers for First Order Plus Time Delay Models
Using Dimensional Analysis”, The fourth International
Conference on Control and Automation (ICCA’03),
Montreal, Canada, 2003.
[5] S., Skogestad, “Simple Analytic Rules for Model
Reduction and PID Controller Tuning”, Journal of
Process Control, Vol: 13, pp.291-309, 2003.
[6] V.N., Vapnik “The Nature of Statistical Learning
Theory”, Springer-Verlag, New York. 1995.
[7] V.N., Vapnik “Statistical Learning Theory”, John Wiley
and Sons, New York. 1998.
[8] N., Cristianini, J., Shawe-Taylor, “An Introduction to
Support Vector Machines and Other Kernel-Based
Learning Methods”, Cambridge University Press,
Cambridge, 2000.
[9] L, Zhao, J, Sun, KR. Butts, “Linear programming support
vector regression with wavelet kernel: A new approach
to nonlinear dynamical systems identification”,
Mathematics and Computers in Simulation,
2009;79:2051–2063.
[10] S., Iplikci, “A support vector machine based control
application to the experimental three-tank system”, ISA
Transactions 2010;49:376-386.
[11] A.J., Smola, B., Schoelkopf, “A tutorial on support
vector regression”, NeuroCOLT2 Technical Report NCTR-
98-030, Royal Holloway College, University of
London, UK. 1998.
[12] J., Ma, J., Theiler, S., Perkins, “Accurate on-line support
vector regression”, Neural Computation, vol.15, p:
2683-2703, 2003.
[13] H., Zhang, X., Wang, C., Zhang, X., Xu, “Modeling
Nonlinear Dynamical Systems Using Support Vector
Machine”, Proceeding of 4. International Conf. On
Machine Learning and Cybernetics, p:3204-3209, 2005.
Rana Ortac-Kabaoglu was born and grown in
Istanbul. After she completed Istanbul
University Depeartment of Electrical-
Electronics Engineering, she had BSc degree
from the same department. She got her PhD.
degree from Istanbul Technical University,
Control Engineering Department. She has been
studying on control theory and its applications.
Rana Ortac-Kabaoglu is also working in
Istanbul University Electrical-Electronics Engineering as a
research assistant.