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A novel methodology for uncertain nonlinear tracking control systems: Exponential convergence manifold approach

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  • Sun, Yeong-Jeu

Abstract

In this paper, we present a novel methodology, for exponential convergence manifold control (ECMC) methodology, to investigate the tracking control of a class of uncertain systems. An ECMC law will drive the plant’s error trajectory exponentially not only to a specific manifold in the error space, but also to the origin, if the exponential convergence condition is satisfied. A numerical example is also provided to illustrate the methodology.

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  • Sun, Yeong-Jeu, 2008. "A novel methodology for uncertain nonlinear tracking control systems: Exponential convergence manifold approach," Chaos, Solitons & Fractals, Elsevier, vol. 36(5), pages 1419-1424.
    • Handle: RePEc:eee:chsofr:v:36:y:2008:i:5:p:1419-1424
    DOI: 10.1016/j.chaos.2006.09.011
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    References listed on IDEAS

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    1. Wang, Jiang & Qiao, Guo-Dong & Deng, Bin, 2005. "Observer-based robust adaptive variable universe fuzzy control for chaotic system," Chaos, Solitons & Fractals, Elsevier, vol. 23(3), pages 1013-1032.
    2. Zhou, Jin & Chen, Tianping & Xiang, Lan, 2006. "Robust synchronization of delayed neural networks based on adaptive control and parameters identification," Chaos, Solitons & Fractals, Elsevier, vol. 27(4), pages 905-913.
    3. Yan, Jun-Juh & Shyu, Kuo-Kai & Lin, Jui-Sheng, 2005. "Adaptive variable structure control for uncertain chaotic systems containing dead-zone nonlinearity," Chaos, Solitons & Fractals, Elsevier, vol. 25(2), pages 347-355.
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