【摘要】 针对换热站质调、量调通道之间的耦合作用和控制模型参数时变的问题,提出一种新的神经网络:模糊PID换热站控制器结构。通过现场采集换热站质调、量调通道阶跃信号响应,并利用最小二乘辨识得到质调、量调通道的控制模型。利用得到的质调、量调通道控制模型,对设计的神经网络:模糊PID控制器进行仿真实验,仿真研究表明该控制器能够有效实现质调、量调通道的解耦,减小控制模型时变对控制品质的影响。更多还原

【Abstract】 Consider the coupling between quality and quantity channels as well as control model time-varying characteristic in heat exchange station,a novel structure of heat exchange station controller based on neural network-fuzzy PID control was proposed.Establishing control model of quality and quantity by using on-site collected step response data and least square method.On this basis,simulation experiments were carried out to the designed controller.Simulation shows that satisfactory performances can be obtained using the designed controller in decoupling of quality and quantity channel,reducing impacts on the control of model time-varying.更多还原