Command filters are essential for alleviating the inherent computational complexity (ICC) of the standard backstepping control method. This paper addresses the synchronization control scheme for an uncertain fractional-order chaotic system (FOCS) subject to unknown dead zone input (DZI) based on a fractional-order command filter (FCF). A virtual control function (VCF) and its fractional-order derivative are approximated by the output of the FCF. In order to handle filtering errors and obtain good control performance, an error compensation mechanism (ECM) is developed. A radial basis function neural network (RBFNN) is introduced to relax the requirement of the uncertain function must be linear in the standard backstepping control method. The construction of a VCF in each step satisfies the Lyapunov function to ensure the stability of the corresponding subsystem. By using the bounded information to cope with the unknown DZI, the stability of the synchronization error system is guaranteed. Finally, simulation results verify the effectiveness of our methods.

命令过滤器对于减轻标准反推控制方法的固有计算复杂性（ICC）是必不可少的。本文提出了一种基于分数阶命令滤波器（FCF）的未知死区输入（DZI）的不确定分数阶混沌系统（FOCS）的同步控制方案。虚拟控制函数（VCF）及其分数阶导数由FCF的输出近似。为了处理过滤错误并获得良好的控制性能，开发了一种错误补偿机制（ECM）。引入了径向基函数神经网络（RBFNN），以放松标准backstepping控制方法中不确定函数必须是线性的要求。每个步骤中VCF的构造都满足Lyapunov功能，以确保相应子系统的稳定性。通过使用有界信息来处理未知DZI，可以确保同步错误系统的稳定性。最后，仿真结果验证了我们方法的有效性。