Abstract
This paper proposes a finite series expansion to approximate general nonlinear dynamics models to arbitrary accuracy. The method produces an approximation of nonlinear dynamics in the form of an aggregate of linear models, weighted by unimodal basis functions, and results in a linear growth bound on the approximation error. Furthermore, this paper demonstrates that the proposed approximation satisfies the modeling assumptions for analysis based on linear matrix inequalities and hence widens the applicability of these techniques to the area of nonlinear control.
Issue Section:
Technical Papers
1.
Liu
, R.
, Saeks
, R.
, and Leake
, R. J.
, 1969, “On Global Linearization
,” SIAM-AMS Proc.
0080-5084, 3
, pp. 93
–102
.2.
Takagi
, T.
, and Sugeno
, M.
, 1985, “Fuzzy Identification of Systems and Its Applications to Modeling and Control
,” IEEE Trans. Syst. Man Cybern.
0018-9472, 15
(1
), pp. 116
–132
.3.
Johansen
, T.
, 1994, “Fuzzy Model Based Control: Stability, Robustness, and Performance Issues
,” IEEE Trans. Fuzzy Syst.
1063-6706, 2
(3
), pp. 221
–232
.4.
Wang
, L. X.
, and Mendel
, J. M.
, 1992, “Fuzzy Basis Functions, Universal Approximators and Orthogonal Least-Squares Learning
,” IEEE Trans. Neural Netw.
1045-9227, 3
, pp. 807
–814
.5.
Chen
, S.
, Cowan
, C. F. N.
, and Grant
, P. M.
, 1991, “Orthogonal Least Squares Learning Algorithms for Radial Basis Function Networks
,” IEEE Trans. Neural Netw.
1045-9227, 2
(2
), pp. 302
–309
.6.
Li
, C. J.
, and Huang
, T.-Y.
, 2000, “Nonlinear Continuous Dynamic System Identification by Automatic Localized Modeling
,” ASME J. Dyn. Syst., Meas., Control
0022-0434, 122
(6
), pp. 354
–358
.7.
Chen
, S.
, Billings
, S. A.
, and Luo
, W.
, 1989, “Orthogonal Least Squares Methods and Their Application to Non-Linear System Identification
,” Int. J. Control
0020-7179, 50
(5
), pp. 1873
–1896
.8.
Kerschen
, G.
, Lenaerts
, V.
, Marchesiello
, S.
, and Fasana
, A.
, 2001, “A Frequency Domain Versus a Time Domain Identification Technique for Nonlinear Parameters Applied to Wire Rope Isolators
,” ASME J. Dyn. Syst., Meas., Control
0022-0434, 123
(12
), pp. 645
–650
.9.
Leontaritis
, I. J.
, and Billings
, S. A.
, 1985, “Input-Output Parametric Models for Non-Linear Systems, Part I: Deterministic Non-Linear Systems
,” Int. J. Control
0020-7179, 41
(2
), pp. 303
–328
.10.
Leontaritis
, I. J.
, and Billings
, S. A.
, 1985, “Input-Output Parametric Models for Non-Linear Systems, Part II: Stochastic Non-Linear Systems
,” Int. J. Control
0020-7179, 41
(2
), pp. 329
–344
.11.
Desrochers
, A.
, and Mohseni
, S.
, 1984, “On Determining the Structure of a Non-Linear System
,” Int. J. Control
0020-7179, 40
(5
), pp. 923
–938
.12.
Banerjee
, A.
, Arkun
, Y.
, Ogunnaike
, B.
, and Pearson
, R.
, 1997, “Estimation of Nonlinear Systems Using Linear Multiple Models
,” AIChE J.
0001-1541, 43
(5
), pp. 1204
–1226
.13.
Johansen
, T.
, and Foss
, B. A.
, 1993, “Constructing NARMAX Models Using ARMAX Models
,” Int. J. Control
0020-7179, 58
(5
), pp. 1125
–1153
.14.
Johansen
, T.
and Foss
, B. A.
, 1995, “Identification of Non-Linear System Structure and Parameters Using Regime Decomposition
,” Automatica
0005-1098, 31
(2
), pp. 321
–326
.15.
Kiriakidis
, K.
, 2003, “On the Expansion of Nonlinear Models Using Bell-Shaped Basis Functions
,” Proceedings of the ASME International Mechanical Engineering Congress and Exposition
, Washington, D.C.
, Nov., pp. 879
–884
.16.
Kiriakidis
, K.
, 2005, “Mixed Mathematical and Physical Modeling for Nonlinear Systems
,” Proceedings of the ASME International Mechanical Engineering Congress and Exposition
, Orlando, FL
, Nov.17.
Wang
, H. O.
, Tanaka
, K.
, and Griffin
, M. F.
, 1996, “An Approach to Fuzzy Control of Nonlinear Systems: Stability and Design Issues
,” IEEE Trans. Fuzzy Syst.
1063-6706, 4
(1
), pp. 14
–23
.18.
Kiriakidis
, K.
, 1999, “Non-Linear Control System Design Via Fuzzy Modelling and LMIS
,” Int. J. Control
0020-7179, 72
(7
), pp. 676
–685
.19.
Vidyasagar
, M.
, 1993, Nonlinear Systems Analysis
, 2nd ed., Prentice-Hall International
, Englewood Cliffs, NJ
.20.
21.
Lancaster
, P.
, and Tismenetsky
, M.
, 1985, The Theory of Matrices
, 2nd ed., Academic
, San Diego, CA
.22.
Lakshmanan
, N. M.
, and Arkun
, Y.
, 1999, “Estimation and Model Predictive Control of Non-Linear Batch Processes Using Linear Parameter Varying Models
,” Int. J. Control
0020-7179, 72
(7
), pp. 659
–675
.23.
Cannon
, R. H.
, 1967, Dynamics of Physical Systems
, McGraw-Hill
, New York
.24.
Boyd
, S.
, El Ghaoui
, L.
, Feron
, E.
, and Balakrishnan
, V.
, 1994, Linear Matrix Inequalities in System and Control Theory
, SIAM
, Philadelphia, PA
.25.
Gahinet
, P.
, Nemirovski
, A.
, Laub
, A.
, and Chilali
, M.
, 1995, LMI Control Toolbox
, The MathWorks
, Natick, MA
.26.
Kiriakidis
, K.
, 2001, “Robust Stabilization of the Takagi-Sugeno Fuzzy Model Via Bilinear Matrix Inequalities
,” IEEE Trans. Fuzzy Syst.
1063-6706, 9
(2
), pp. 269
–277
.27.
Aizerman
, M. A.
, and Gantmacher
, F. R.
, 1964, Absolute Stability of Regulator Systems
, Holden-Day
, San Francisco
.28.
Johansson
, M.
, and Rantzer
, A.
, 1998, “Computation of Piecewise Quadratic Lyapunov Functions for Hybrid Systems
,” IEEE Trans. Autom. Control
0018-9286, 43
(4
), pp. 555
–559
.29.
Shamma
, J.
, and Cloutier
, J. R.
, 1993, “Gain-Scheduled Missile Autopilot Design Using Linear Parameter Varying Transformation
,” J. Guid. Control Dyn.
0731-5090, 16
(2
), pp. 256
–263
.30.
Apkarian
, P.
, Gahinet
, P.
, and Becker
, G.
, 1995, “Self-Scheduled H∞ Control of Linear Parameter-Varying Systems: A Design Example
,” Automatica
0005-1098, 31
(9
), pp. 1251
–1261
.Copyright © 2007
by American Society of Mechanical Engineers
You do not currently have access to this content.