【摘要】 通过将BP神经网络和常规PID控制器结合,提出了一种新的火电厂超临界机组过热汽温控制方案。将这种方法应用于主汽温控制,可以有效克服过热汽温对象的大滞后和大惯性,并能够克服对象在运行中参数变化的影响,获得良好的控制品质。仿真试验表明:所设计的系统在控制品质、鲁棒性方面明显优于常规PID控制系统。更多还原

【Abstract】 By combining the BP neural network with conventional PID controller, a new temperature control strategy of superheated steam in supercritical electric power plant is put forward. This scheme can effectively overcome the large time delay and inertia of the superheated steam and the influence of object in varying operational parameters, thus excellent control quality is obtained. Through simulation in various situations, it validates that the control quality and the robustness of this control system are apparently superior to the conventional PID control system.更多还原