基于神经网络PID控制器的混沌系统控制与同步

Control and synchronization of chaos systems based on neural network PID controller

提出了一种基于神经网络参数自整定PID控制器的混沌控制方法。该方法由神经网络辨识器和神经网络控制器组成,神经网络学习算法均采用Davidon最小二乘法。考虑到混沌系统的动力学特性,施加单个控制量可实现模型未知混沌系统的平衡点镇定和自同步,仿真结果证实了该方法的有效性。

An self-correction PID chaos control scheme consisting of neural network identifier and neural network controller was presented. Davidon least square method was used to learning weights of two neural networks. Considering dynamic characters of multi-variable chaos system, the chaos system can implement fixed point control and synchronization by controlling single variable. The effectiveness of the proposed control method was verified by numerical simulations.