Nuclear power device two-loop multi-variable integrated model fuzzy predication control method
An integrated model and fuzzy prediction technology, applied in the field of control, can solve the problems of long stabilization time and large overshoot of system parameters.
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[0090] The present invention is described in more detail below in conjunction with accompanying drawing example:
[0091] 1 Training of static DLF neural network
[0092] The opening degree of the nozzle valve cam angle Δθ and the water supply valve opening degree Δ of the nuclear power plant secondary circuit are used as the input of the DLF network; the intermediate variable x of the nonlinear link 1 and x 2 Output for the DLF network. The BP in the DLF network adopts a 2-10-2 network structure. After 25,000 times of training, the cumulative error does not exceed the expected error.
[0093] Let the threshold of the jth unit of the output layer be r j , the connection matrix W∈R between the units of the output layer and the hidden layer H p×2 ,
[0094] And the connection matrix W between the output layer and the input layer U F ; The connection matrix V∈R between the hidden layer and each unit of the input layer U p×2 .
[0095] 1) The weight matrix between the inp...
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