Composite adaptive fuzzy control for synchronizing generalized Lorenz systems
Er, Meng Joo
Date of Issue2012
School of Electrical and Electronic Engineering
This paper presents a methodology of asymptotically synchronizing two uncertain generalized Lorenz systems via a single continuous composite adaptive fuzzy controller (AFC). To facilitate controller design, the synchronization problem is transformed into the stabilization problem by feedback linearization. To achieve asymptotic tracking performance, a key property of the optimal fuzzy approximation error is exploited by the Mean Value Theorem. The composite AFC, which utilizes both tracking and modeling error feedbacks, is constructed by introducing a series-parallel identification model into an indirect AFC. It is proved that the closed-loop system achieves asymptotic stability under a sufficient gain condition. Furthermore, the proposed approach cannot only synchronize two different chaotic systems but also significantly reduce computational complexity and implemented cost. Simulation studies further demonstrate the effectiveness of the proposed approach.
DRNTU::Engineering::Electrical and electronic engineering
© 2012 American Institute of Physics. This paper was published in Chaos and is made available as an electronic reprint (preprint) with permission of American Institute of Physics. The paper can be found at the following official URL: [http://dx.doi.org/10.1063/1.4721901]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.