Output Stable Control Design for a Class of Nonlinear Systems Based on Adaptive Fuzzy Logic Systems

Zi Lin Gao; Yong Pan; Jiang Xiong; Jin Peng Chen

doi:10.4028/www.scientific.net/AMR.945-949.2670

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 945-949Output Stable Control Design for a Class of...

Output Stable Control Design for a Class of Nonlinear Systems Based on Adaptive Fuzzy Logic Systems

Abstract:

The adaptive fuzzy logic systems are constructed in this paper by utilizing the data information sampled from the inputs and outputs of unknown functions in the nonlinear systems controlled, and then output stable controller is synthesized for a class of uncertain nonlinear systems based on the universal approximation property of adaptive fuzzy logic systems. Finally, the simulation shows the validity of the method in this paper.

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Periodical:

Advanced Materials Research (Volumes 945-949)

Pages:

2670-2675

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https://doi.org/10.4028/www.scientific.net/AMR.945-949.2670

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Online since:

June 2014

Authors:

Zi Lin Gao*, Yong Pan, Jiang Xiong, Jin Peng Chen

Keywords:

Adaptive Fuzzy Logic Systems, Fuzzy Control, Nonlinear System, Output Stable

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References

[1] Ding Z T. Output regulation of uncertain nonlinear systems with nonlinear exosystems. IEEE Trans. On Automatic Control, 2006, 51(1): 498-503.

DOI: 10.1109/tac.2005.864199

Google Scholar

[2] Eduardo D. Sontag, Wang Y. Notions of input to output stability. Systems & Control Letters, 1998, 38: 235-248.

DOI: 10.1016/s0167-6911(99)00070-5

Google Scholar

[3] Wang L X, Mendel J M. Fuzzy basis functions, universal approximation and orthogonal least squares learning. IEEE Trans. On Neural Networks, 1992, 3(5): 807–814.

DOI: 10.1109/72.159070

Google Scholar

[4] Wang Y H, Li Z Y. Adaptive tracking control for a class of nonlinear systems based on fuzzy logic systems. Control and Decision, 2004, 19(10): 1121-1124.

Google Scholar

[5] Kim J H, Park C W, Kim E, Park M. Fuzzy adaptive synchronization of uncertain chaotic systems. Physics Letters A, 2005, 334(9): 295–305.

DOI: 10.1016/j.physleta.2004.11.033

Google Scholar

[6] Tong S C, Li Q G, Chai T Y. Fuzzy adaptive control for a class of nonlinear systems. Fuzzy Sets and Systems, 1999, 101(1): 31-39.

DOI: 10.1016/s0165-0114(97)00055-9

Google Scholar

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

DOI: 10.1109/91.227383

Google Scholar

[8] Vassilis K, Ilias P, John N.L. Intelligent classification using adaptive fuzzy logic systems/Proceeding of the 4th International IEEE Conference on Intelligent Systems, Sept. 6-8, 2008, Varna, Bulgaria: IEEE, 2008: 8-13.

DOI: 10.1109/is.2008.4670453

Google Scholar

[9] Zhang L Q, Shao C. An adaptive learning method for the generation of fuzzy inference system from data. ACTA AUTOMATICA SINICA, 2008, 34(1): 80-84.

DOI: 10.3724/sp.j.1004.2008.00080

Google Scholar

[10] Zu J K, Dai G Z, Lu J C. Robust learning algorithm for adaptive fuzzy logical systems. Control and Decision, 2003, 18(1): 67-72.

Google Scholar

[11] Wang L X. Stable adaptive fuzzy controllers with application to inverted pendulum tracking. IEEE Trans. On Systems, Man, and Cybernetics, 1996, 26(5): 677-691.

DOI: 10.1109/3477.537311

Google Scholar