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To improve the Superheater Steam Temperature (SST) control of a large-scale supercritical coal-fired boiler generating unit, this paper presents an inverse compensation control scheme based on dynamic recurrent neural network (NN) inverse process models for the multi-stage water-spray desuperheating controllers. With proper analysis of the boiler design and operational characteristics, the inputs...
An Inverse Dynamic Neuro-Controller (IDNC) is developed to improve the superheater steam temperature control of a 300MW boiler unit. A recurrent neural network was used for building the Inverse Dynamic Process Models (IDPMs) for the superheater system. Two inverse dynamic neural network (NN) models referring to the first-stage and the second-stage water-spray attemperators are constructed separately...
This paper presents an approach for control and system identification using Diagonal Recurrent Neural Networks (DRNN). An unknown plant is identified by a Diagonal Recurrent Neuroidentifier (DRNI), and provides the sensitivity information of the plant to a Diagonal Recurrent Neurocontroller (DRNC). A dynamic backpropagation (DBP), is developed to train both DRNC and DRNI. The DRNN captures the dynamic...
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