Duffing系统的控制研究

Research on the Control of Duffing System

对Duffing混沌系统采用基于RBF神经网络逼近非线性项的滑模控制方法,设计了系统的控制输入和RBF神经网络的自适应律,然后从理论上对系统进行稳定性分析,构造Lyapunov函数,通过理论推导证明了在所设计的控制输入和RBF自适应律作用下,系统在原点是渐近稳定的.最后仿真结果证明了该方法的有效性,利用该方法可以实现对周期信号的快速稳定跟踪,达到了控制目的.

Adopting a sliding mode control method for Duffing chaotic system based on RBF neural network approximating non-linear term.We designed the control input of the system and the adaptive law of RBF neural Network.Then the stability of the system is analyzed theoretically and the Lyapunov function is constructed.By theoretical derivation,it is proved that the system is asymptotically stable at the origin under the designed control input and RBF adaptive law.Finally,the simulation results prove the effectiveness of the method.The method can realize the fast and stable tracking of periodic signals and achieve the control purpose.