基于遗传算法的航空发动机状态变量模型建立方法
Aero-Engine State Variable Modeling Based on the Genetic Algorithm
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摘要: 提出了一种采用遗传算法建立用于航空发动机控制系统设计的小偏差状态变量模型的方法,即根据发动机稳态工作点处的线性化数学模型的动态响应应该与该稳态工作点处的非线性数学模型动态响应一致的原则来构造遗传算法的适应度函数,通过优化算法,得出系统的状态变量模型。该方法不受系统模态及模型阶次的限制。应用该方法建立某型涡扇发动机的小偏差状态变量模型,具有较高的建模精度,根据该状态变量模型设计鲁棒控制器取得了良好的控制效果,从而验证了该方法的有效性。Abstract: Based on the Genetic Algorithm(GA),aero-engine small perturbation State Variable Model(SVM) was proposed.The fitness function of GA was established according to the principle that the aero-engine dynamic responses of the linear model should be in accordance with that of the nonlinear model at the same steady working point.Using the optimization algorithm,the SVM can be obtained.This method has no limitation on the system modes and orders.The SVM of some turbofan engine established with this method turns out to have high accuracy.The performance of the robust controller based on this SVM is quite well,which indicates the validity of this method.
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Key words:
- aerospace propulsion system /
- aero-engine /
- state variable model /
- modeling /
- genetic algorithm
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