基于神经网络逆控制的水轮机调节系统

根据神经网络对非线性系统模型的辨识能力,将其与自适应逆控制相结合,对水轮发电机组的逆模型进行建模,构建一种新的水轮机调节系统。该方案以逆系统以及系统辨识理论为基础,以水轮发电机组作为被控对象,分别针对其频率和负荷扰动,建立神经网络在线逆控制器,对系统进行调控,并将仿真结果与传统PID控制进行比较。从仿真结果可以看出,所提的控制方案能够实现对水轮发电机组的有效控制,使系统具有较好的动态性能和鲁棒性。

Hydraulic Turbine Governing System Based on Neural Network Inverse Control

According to the identification ability of neural network to the model of non-linear system,the inverse model of hydraulic turbine generator unit is modeled by combining the neural network with the adaptive inverse control,and a new turbine regulating system is born. Based on the theory of inverse system and system identification,a neural network inverse controller is established for the frequency and load disturbance of the hydraulic turbine generator unit,and the simulation results are compared with the traditional PID control. From the simulation results,it can be seen that the proposed control scheme can effectively control the hydraulic turbine generator unit and make the system have better dynamic performance and robustness.