航空发动机多变量三层神经网络控制

MULTIVARIABLE CONTROL FOR AEROENGINE WITH 3-LAYER NEURAL NETWORKS

提出了一种发动机多变量神经网络控制方法。采用三层前向神经网络对非线性项进行补偿，神经网络权重自适应律采用在线学习算法。控制系统的设计不需要知道精确模型，适应于全飞行包线。仿真研究表明发动机多变量神经网络控制具有良好的动、静态性能。

A multivariable neural network adaptive control is provided for a turbofan engine.The nonlinear system is compensated dynamically by a 3-layer neural network.An on-line weight-tuning algorithm with simplified Hebbian rule and e-modification is worked out to guarantee tracking performance as well as bounded weights without off-line training.The precise model of the engine is not necessary for design of control system.The multivariable control system has satisfactory performance for the full flight envelope with good adaptation and robustness. Simulation results show satisfactory dynamic and static performance within the whole flight envelope and good effectiveness of reducing interaction in the multivariable system with significant coupling.