Generalized Projective Synchronization of Chaotic Heavy Gyroscope Systems via Sliding Rule-Based Fuzzy Control
Author(s) -
Faezeh Farivar,
Mahdi Aliyari Shoorehdeli,
Mohammad Ali Nekoui,
Mohammad Teshnehlab
Publication year - 2012
Publication title -
isrn artificial intelligence
Language(s) - English
Resource type - Journals
eISSN - 2090-7443
pISSN - 2090-7435
DOI - 10.5402/2012/576873
Subject(s) - control theory (sociology) , chaotic , controller (irrigation) , synchronization of chaos , lyapunov stability , lyapunov exponent , mathematics , lyapunov function , synchronization (alternating current) , jacobian matrix and determinant , nonlinear system , fuzzy logic , computer science , topology (electrical circuits) , control (management) , physics , artificial intelligence , quantum mechanics , combinatorics , agronomy , biology
This paper proposes the generalized projective synchronization for chaotic heavy symmetric gyroscope systems versus external disturbances via sliding rule-based fuzzy control. Because of the nonlinear terms of the gyroscope, the system exhibits complex and chaotic motions. Based on Lyapunov stability theory and fuzzy rules, the nonlinear controller and some generic sufficient conditions for global asymptotic synchronization are attained. The fuzzy rules are directly constructed subject to a common Lyapunov function such that the error dynamics of two identical chaotic motions of symmetric gyros satisfy stability in the Lyapunov sense. The proposed method allows us to arbitrarily adjust the desired scaling by controlling the slave system. It is not necessary to calculate the Lyapunov exponents and the Eigen values of the Jacobian matrix. It is a systematic procedure for synchronization of chaotic systems. It can be applied to a variety of chaotic systems no matter whether it contains external excitation or not. It needs only one controller to realize synchronization no matter how much dimensions the chaotic system contains, and the controller is easy to be implemented. The designed controller is robust versus model uncertainty and external disturbances. Numerical simulation results demonstrate the validity and feasibility of the proposed method.
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