流量可调燃气发生器压强控制仿真

摘要

为了提高流量可调燃气发生器的流量控制效果,建立了燃气发生器流量调节系统动态模型.针对燃气发生器流量调节系统时变性的特点,引入了一种基于神经网络PI(比例积分)算法的压强控制系统;研究了不同自由容积条件下神经网络PI控制系统与PI控制系统控制效果的有效性,得到了控制器的压强工作范围.不同自由容积条件下的2种算法的仿真结果表明:基于神经网络PI算法的压强控制系统响应速度较快,压力超调量较小,压强工作范围大,系统的动态特性较好,能更好地解决燃气发生器流量调节系统时变性带来的控制精度差的问题.%In order to improve the control effect of adjustable flow gas generator,a dynamic model for the adjustable-flow gas generator was built. According to the time-varying characteristics of the gas generator system,a pressure control system based on neural network PI( proportional plus integral) algorithm was designed. The control accuracy of neural networks PI algorithm and PI algorithm were studied under the conditions of different free-volume,and the pressure operating range of two controllers were obtained. The results under different working-conditions show that the pressure control system based on neural network PI algorithm has faster response speed,less pressure overshoot,wider pressure operating range and better dynamic characteristics,so the control problems caused by time-varying characteristics of the adjustable-flow gas generator system can be solved effectively.