Portal de Periódicos da CAPES

Composite adaptive fuzzy control for synchronizing generalized Lorenz systems

2012; American Institute of Physics; Volume: 22; Issue: 2 Linguagem: Inglês

10.1063/1.4721901

1527-2443

Yongping Pan, Meng Joo Er, Tairen Sun,

Neural Networks Stability and Synchronization

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.