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TRACKING CONTROL OF NONLINEAR SYSTEMS: A SLIDING MODE DESIGN VIA CHAOTIC OPTIMIZATION

ZHAO LU

Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204-4005, USA

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LEANG-SAN SHIEH

Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204-4005, USA

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, and

JAGDISH CHANDRA

School of Engineering and Applied Sciences, George Washington University, Washington DC 20052, USA

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https://doi.org/10.1142/S0218127404009909Cited by:6 (Source: Crossref)

Abstract

The output tracking for a general family of nonlinear systems presents formidable technical challenges. In this paper, we present a novel scheme for tracking control of a class of affine nonlinear systems with multi-inputs. This effective procedure is based on a new sliding mode design for tracking control of such nonlinear systems. The construction of an optimal sliding mode is a difficult problem and no systematic and efficient method is currently available. Here, we develop an innovative approach that utilizes a chaotic optimizing algorithm, which is then successfully applied to obtain the optimal sliding manifold. The existing efficient reaching law approach is then utilized to synthesize the sliding mode control law. The sliding mode control scheme proposed here is particularly appropriate for robust tracking of the chaotic motion trajectory.

Supported by the US Army Research Office under Grant DAAD 19-02-1-0321.

Keywords:

References

G. Chen and T. Ueta, Int. J. Bifurcation and Chaos 9, 1465 (1999). Link, Web of Science, Google Scholar
C. M. Dorling and A. S. I. Zinober, Int. J. Contr. 44, 65 (1986). Crossref, Web of Science, Google Scholar
L. C. Fu and T. L. Liao, IEEE Trans. Automat. Contr. 35, 1345 (1990). Crossref, Web of Science, Google Scholar
W. B. Gao and J. C. Hung, IEEE Trans. Indust. Electron. 40, 45 (1993). Web of Science, Google Scholar
S. M. Guoet al., IEEE Trans. Circuits Syst. 47, 1557 (2000). Crossref, Google Scholar
M. Hasegawa, T. Ikeguchi and K. Aihara, Neural Networks 15, 271 (2002). Crossref, Web of Science, Google Scholar
J. H. Holland , Adaptation in Natural and Artificial Systems ( The University of Michigan Press , Ann Arbor, MI , 1975 ) . Google Scholar
J. Y. Hung, W. B. Gao and J. C. Hung, IEEE Trans. Indust. Electron. 40, 2 (1993). Crossref, Web of Science, Google Scholar
Z. P. Jiang, IEEE Trans. Circuits Syst. 49, 244 (2002). Crossref, Google Scholar
O. Kaynak, IEEE Trans. Indust. Electron. 48, 4 (2001). Crossref, Web of Science, Google Scholar
S. Kirkpatrick, J. C. D. Gellatt and M. P. Vecchi, Science 220, 671 (1983). Crossref, Web of Science, Google Scholar
H. G. Kwatny and H. Kim, Variable structure control of partially linearizable dynamics, Proc. American Control Conf. (1989) pp. 1148–1153. Google Scholar
T. Kwok and K. A. Smith, Neural Networks 13, 731 (2000). Crossref, Web of Science, Google Scholar
B. Li and W. S. Jiang, Cybern. Syst. 29, 409 (1998). Web of Science, Google Scholar
D. Li and J. E. Slotine, On sliding control for multi-input multi-output nonlinear systems, Proc. American Control Conf. (1987) pp. 874–879. Google Scholar
S. Mascolo and G. Grass, Int. J. Bifurcation and Chaos 9, 1425 (1999). Link, Web of Science, Google Scholar
H. Sira-Ramirez, IEEE Trans. Automat. Contr. 34, 1186 (1989). Crossref, Web of Science, Google Scholar
W. C. Su, S. V. Drakunov and U. Ozguner, Automatica 32, 925 (1996). Crossref, Web of Science, Google Scholar
T. Ueta and G. Chen, Int. J. Bifurcation and Chaos 10, 1917 (2000). Link, Web of Science, Google Scholar
V. I. Utkin, IEEE Trans. Automat. Contr. 22, 212 (1977). Crossref, Web of Science, Google Scholar
V. I. Utkin and K. D. Young, Automat. Remote Contr. 39, 1466 (1979). Web of Science, Google Scholar
H. T. Yau, C. K. Chen and C. L. Chen, Int. J. Bifurcation and Chaos 10, 1139 (2000). Link, Web of Science, Google Scholar