航空发动机神经网络反步控制方法
Backstepping control strategy for aero-engine using neural networks
-
摘要: 针对航空发动机非线性和不确定性的特点,提出了一种基于神经网络的反步控制方法.采用径向基神经网络估计未知系统方程,并用一种平滑切换法有效避免了控制器奇异问题.反步法的设计基于Lya-punov稳定性原理,保证了闭环系统一致渐近有界.最后针对某型涡扇发动机非线性模型设计了高压转速控制器,仿真结果验证了该方法的有效性.Abstract: A Backstepping control strategy based on neural network was presented in view of nonlinearity and uncertainty of aero-engine.Radial basis function(RBF) neural network was used to estimate the equations of the unknown system,and a smooth-switching algorithm was proposed to avoid singularity phenomenon.Using Lyapunov stability analysis,the uniformly ultimately boundedness of closed-loop systems was proven.Finally,the compressor speed controller was designed based on a nonlinear model of some turbofan engine.The simulation results illustrate the effectiveness of the proposed approach.
-
Key words:
- aero-engine /
- nonlinear system /
- neural network /
- backstepping control
点击查看大图
计量
- 文章访问数: 1293
- HTML浏览量: 2
- PDF量: 483
- 被引次数: 0