基于自适应RBF神经网络PID控制微燃机排气温度

Control of exhaust gas temperature of micro-combustion engine based on adaptive RBF neural network

为了获得更好的微燃机性能,需要对排气温度进行很好的控制,采用自适应RBF神经网络PID控制器进行控制。建立了微型燃气轮机排气温度控制的数学模型,给出了一般的RBF神经网络,并引入径向基函数神经网络对PID控制的参数进行调整。通过将其应用于排气温度控制来证明所提出的控制策略的有效性。通过仿真模拟,排气控制系统的动态响应可以有效地提高,并且所提出的控制器的抗扰动性优于PID控制器。

In order to obtain better micro gas turbine performance,it is need to control exhaust gas temperature,using adaptive RBF neural network PID controller.This paper established a mathematical model of microcombustion exhaust temperature control,general RBF neural network are given,and radial basis function(RBF)neural network is introduced to adjust the parameters of the PID control.Those are applied to exhaust temperature control to prove the effectiveness of the proposed control strategy.Through simulation,the dynamic response of the control system of exhaust gas can be effectively improved,and the disturbance resistance of the proposed controller is better than PID controller.