Chaos synchronization based on unknown input proportional multiple-integral fuzzy observer
Journal article, Peer reviewed
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Original versionYoussef, T., Chadli, M., Karimi, H. R., & Zelmat, M. (2013). Chaos synchronization based on unknown input proportional multiple-integral fuzzy observer. Abstract and Applied Analysis, 2013, 1-11. doi: 10.1155/2013/670878 10.1155/2013/670878
This paper presents an unknown input Proportional Multiple-Integral Observer (PIO) for synchronization of chaotic systems based on Takagi-Sugeno (TS) fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is regarded as a message encoded in the chaotic system and recovered by the proposed PIO. Both states and outputs of the fuzzy chaotic models are subject to polynomial unknown input with kth derivative zero. Using Lyapunov stability theory, sufficient design conditions for synchronization are proposed. The PIO gains matrices are obtained by resolving linear matrix inequalities (LMIs) constraints. Simulation results show through two TS fuzzy chaotic models the validity of the proposed method.
Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2013/670878 Open Access