摘要
利用一个BP网络作为某双转子涡轮发动机的控制器,利用另一个BP网络做为非线性对象的映射器,仿真结果表明本控制结构具有较强的控制鲁棒性并有较好的应用前景。
A BP(back propagation)neural network is used as the controller of a two spool turbo jet engine. Because the neural network adjusts its weights by using gradient algorithm, the partial derivatives of the outputs to the inputs of the plant are needed. However, the partial derivatives of a complicated thermal system are very difficult to be presolved precisely , and thus another neural network is added to the control system and acts as a mapper of the nonlinear plant composed of the engine and its fuel auxiliary. The simulation results show that the control structure does not need any model parameters of the plant and is of stronger robustness.
出处
《航空学报》
EI
CAS
CSCD
北大核心
1997年第2期231-233,共3页
Acta Aeronautica et Astronautica Sinica