Zhengzhou Preschool Education College, Zhengzhou 450099, China.
Comput Intell Neurosci. 2021 Oct 21;2021:8962251. doi: 10.1155/2021/8962251. eCollection 2021.
An adaptive neural network (NN) backstepping control method based on command filtering is proposed for a class of fractional-order chaotic systems (FOCSs) in this paper. In order to solve the problem of the item explosion in the classical backstepping method, a command filter method is adopted and the error compensation mechanism is introduced to overcome the shortcomings of the dynamic surface method. Moreover, an adaptive neural network method for unknown FOCSs is proposed. Compared with the existing control methods, the advantage of the proposed control method is that the design of the compensation signals eliminates the filtering errors, which makes the control effect of the actual system improve well. Finally, two examples are given to prove the effectiveness and potential of the proposed method.
本文针对一类分数阶混沌系统(FOCSs),提出了一种基于指令滤波的自适应神经网络(NN)反步控制方法。为了解决经典反步方法中项爆炸的问题,采用了指令滤波方法,并引入误差补偿机制来克服动态面方法的缺点。此外,还提出了一种用于未知 FOCSs 的自适应神经网络方法。与现有控制方法相比,所提出的控制方法的优点在于补偿信号的设计消除了滤波误差,从而使实际系统的控制效果得到了很好的改善。最后,通过两个实例验证了所提出方法的有效性和潜力。