摘要
经典 PID方法的控制参数难以精确整定 ,且依赖于对象的数学模型 ,故自适应性较差 ,很难适应具有非线性、时变不确定性的被控对象 ,控制精度难以保证。文中研究了在近似参数 PID控制基础之上 ,采用 RBF神经网络进行补偿控制的综合控制方法。仿真研究结果表明了该方法的鲁棒性和跟踪性能均优于经典
It is difficult to get classic PID controller's precise parameters,and PID control method is based on the precise mathematical model.Generraly,its adaptivity is poor.So, PID control method is not adaptive to nonlinear and time variant plants.It is impossible to insure the accuracy of the system.This paper study a method, in which classic non precise parameters PID controller's play a important role and RBF neural networks is make used to compensate the PID controller.Simulation results indicated that the system robustness and tracking performance are superior to those of classic PID method.
出处
《电气传动》
北大核心
2000年第5期3-5,共3页
Electric Drive
