In this study, the problem of multi-switching synchronization of the chaotic systems (CSs) with fractional-order dynamics is considered. Unlike to the most studies, the dynamics of slave chaotic systems are unknown and also the master systems are not fixed but are switched between several synchronization modes. A general type-2 (GT2) fuzzy neural network (FNN) is proposed to approximate the unknown nonlinearities. The stability and robustness is investigated by the Lyapunov theorem and the fractional-order adaptation laws are obtained to optimize the rules of GT2FNNs. The robustness of the proposed scheme against approximation errors and variation of synchronization modes is guaranteed by the proposed compensators. The good performance of schemed method is demonstrated by several simulations and comparison with recent presented control techniques.

在这项研究中，考虑了具有分数阶动力学的混沌系统的多开关同步问题。与大多数研究不同，从属混沌系统的动力学是未知的，主系统也不是固定的，而是在几种同步模式之间切换。提出了一种通用的2型（GT2）模糊神经网络（FNN）来近似未知的非线性。利用Lyapunov定理研究了稳定性和鲁棒性，并获得了分数阶自适应定律来优化GT2FNN的规则。所提出的补偿器保证了该方案对逼近误差和同步模式变化的鲁棒性。通过几种仿真以及与最新提出的控制技术的比较，证明了该方法的良好性能。