Adaptive Stable Control for Chaos Systems by New Fuzzy Inference Systems without Any Rule Base

Article Preview

Abstract:

A novel adaptive stability scheme is presented for a class of chaos system with uncertainties. First, the new fuzzy inference systems are employed to approximate uncertainties. Subsequently, the sliding mode controllers are proposed for stability of the chaos systems. Theoretical analysis and numerical simulations show the effectiveness of the proposed scheme.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

367-372

Citation:

Online since:

September 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Wang, L. X., Stable adaptive fuzzy control of nonlinear systems, IEEE Transactions on Fuzzy Systems, 1993, 1(2): 146-155.

DOI: 10.1109/91.227383

Google Scholar

[2] Tong S.C., Tang J.T., Wang T., Fuzzy adaptive control of multivariable nonlinear systems, Fuzzy Sets and Systems, 2000, 111 (2): 153-167.

DOI: 10.1016/s0165-0114(98)00052-9

Google Scholar

[3] Tong S.C., Li Y.M., Observer-based fuzzy adaptive control for strict-feedback nonlinear systems, Fuzzy Sets and Systems, 2009, 160(12): 1749-1764.

DOI: 10.1016/j.fss.2008.09.004

Google Scholar

[4] Chen W.S., Zhang Z.Q., Globally stable adaptive backstepping fuzzy control for output-feedback systems with unknown high-frequency gain sign, Fuzzy Sets and Systems, 2010, 161(6): 821-836.

DOI: 10.1016/j.fss.2009.10.026

Google Scholar

[5] Chen B., Liu X.P., Liu K.F., Shi P., Lin C., Direct adaptive fuzzy control for nonlinear systems with time-varying delays, Information Sciences, 2010, 180(5): 776-792.

DOI: 10.1016/j.ins.2009.11.004

Google Scholar

[6] Luo, L., Wang, Y.H., Fan, Y.Q., Zhang, Y., Adaptive control for a class of nonlinear pure-feedback systems based on partition of unity back-stepping approach, ICIC Express Letters, 2011, 5(3): 707-712.

Google Scholar

[7] Luo, L., Wang, Y.H., Fan, Y.Q., Zhang, Y., Direct Adaptive Control of Nonlinear Strict Feed back Systems Via Backstepping and Partition of Unity Approach, ICIC Express Letters, Part B: Applications,2012, 3: 493-500.

Google Scholar

[8] Zhou S. M., Gan J. Q., Low-level interpretability and high-level interpretability: a unified view of data-driven interpretable fuzzy system modeling, Fuzzy Sets and Systems, 2008, 159: 3091-3031.

DOI: 10.1016/j.fss.2008.05.016

Google Scholar

[9] zhang D. Y., Wang S. T., Han B. and Hu D., a class of new fuzzy inference systems with linearly parameter growth and without any rule base, information technology journal, 2007, 6(5): 704-710.

DOI: 10.3923/itj.2007.704.710

Google Scholar

[10] Wang M. ,Chen B. ,Dai S. L., Direct Adaptive Fuzzy Tracking Control for a Class of Perturbed Strict-Feedback Nonlinear Systems, Fuzzy Sets and Systems,2007,158 (24): 2655-2670.

DOI: 10.1016/j.fss.2007.06.001

Google Scholar

[11] Wang M. ,Chen B. ,Liu X.P., Shi P., Adaptive Fuzzy Tracking Control for a Class of Perturbed Strict-Feedback Nonlinear Time-Delay Systems, Fuzzy Sets and Systems, 2008, 159(8): 949-967.

DOI: 10.1016/j.fss.2007.12.022

Google Scholar

[12] Slotine J. J., Li W., Applied Nonlinear Control, Englewood Cliffs, NJ: Prentice-Hall, (1991).

Google Scholar

[13] Tang Y. Z., Zhang N. Y. and Li Y. D., Stable fuzzy adaptive control for a class of nonlinear systems, Fuzzy Sets and Systems, 1999, 104: 278-288.

DOI: 10.1016/s0165-0114(97)00205-4

Google Scholar

[14] Shahnazi R. and Akbarzadeh-T M. R., Robust PI adaptive fuzzy control with large and fast disturbance rejection for a class of uncertain nonlinear systems, IEEE Trans. Fuzzy Systems, 2008, 1616(1): 187-197.

DOI: 10.1109/tfuzz.2007.903320

Google Scholar