Xiangfan Coal-fired Power Plant, a key energy construction project matched with Three Gorges Project, approved by the State Council. formally started to build in the suburb of Xiangfan City, Hubei Province on November...Xiangfan Coal-fired Power Plant, a key energy construction project matched with Three Gorges Project, approved by the State Council. formally started to build in the suburb of Xiangfan City, Hubei Province on November 29, 1996.展开更多
By combining the Back-Propagation (BP) neural network with conventional proportional Integral Derivative (PID) controller, a new temperature control strategy of the export steam in supercritical electric power pla...By combining the Back-Propagation (BP) neural network with conventional proportional Integral Derivative (PID) controller, a new temperature control strategy of the export steam in supercritical electric power plant is put forward. This scheme can effectively overcome the large time delay, inertia of the export steam and the influencee of object in varying operational parameters. Thus excellent control quality is obtaitud. The present paper describes the development and application of neural network based controller to control the temperature of the boiler's export steam. Through simulation in various situations, it validates that the control quality of this control system is apparently superior to the conventional PID control system.展开更多
文摘Xiangfan Coal-fired Power Plant, a key energy construction project matched with Three Gorges Project, approved by the State Council. formally started to build in the suburb of Xiangfan City, Hubei Province on November 29, 1996.
基金supported by the project of "SDUST Qunxing Program"(No.qx0902075)
文摘By combining the Back-Propagation (BP) neural network with conventional proportional Integral Derivative (PID) controller, a new temperature control strategy of the export steam in supercritical electric power plant is put forward. This scheme can effectively overcome the large time delay, inertia of the export steam and the influencee of object in varying operational parameters. Thus excellent control quality is obtaitud. The present paper describes the development and application of neural network based controller to control the temperature of the boiler's export steam. Through simulation in various situations, it validates that the control quality of this control system is apparently superior to the conventional PID control system.