Aeroengine Separate Decoupling Control Based on Recursive Neural Networks

To solve the problem of coupling in aeroengine multivariable control system,a dynamic decoupling control method based on recursive wavelet neural networks is presented.The structure of engine decoupling control system, as well as its decoupling principle and algorithm,is given.The structure includes two separate control loops.The two recursive wavelet networks,which employed normalized wavelet basic functions,were used as the decoupling identifier,and two PID neural networks were used as the controller.The wavelet networks identify the dynamic model of the engine and feed back the sensitivity information through on-line learning.The neural network PID controller updates the weights adaptively according to the on-line sensed information,and accomplishes self-governed control of each engine control loop.The simulation results of a turbofan engine show that the proposed method can effectively reduce the coupling influence of each control loop and assure satisfactory transient performance.It can be successfully applied to decoupling of aeroengine control system.