| 航空发动机鲁棒自适应反演控制 |
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| 引用本文： | 刘可.航空发动机鲁棒自适应反演控制[J].科学技术与工程,2012,12(1):102-105,136. |
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| 作者姓名： | 刘可 |
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| 作者单位： | 西北工业大学 动力与能源学院,西安,710072 |
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| 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多输入多输出反演控制方法。采用径向基神经网络逼近系统中的不确定性，在控制中引入自适应鲁棒项，以克服系统中不确定性的影响。在递推过程中，虚拟控制量和实际控制量的求取始终基于Lyapunov稳定性原理，从而保证了闭环系统的一致渐近有界。最后针对某型涡扇发动机非线性模型设计了转速控制器，仿真结果验证了该方法的有效性。
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| 关 键 词： | 航空发动机 反演 鲁棒性 自适应 神经网络 |
| 收稿时间： | 2011/10/20 0:00:00 |
| 修稿时间： | 2011/10/20 0:00:00 |
Robustness of adaptive backstepping control for aero-engine |
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| Liu Ke.Robustness of adaptive backstepping control for aero-engine[J].Science Technology and Engineering,2012,12(1):102-105,136. |
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| Authors: | Liu Ke |
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| Institution: | (College of Power and Energy Engineering,Northwestern Polytechnical University,Xi’an 710072,P.R.China) |
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| Abstract: | A multi-input/multi-output(MIMO) backstepping control strategy based on neural network was presented in view of nonlinearity and uncertainty of aero-engine.Radial basis function(RBF) neural networks was used as approximation models for the uncertain of the system, and overcome the uncertainty by introduce a adaptive robustness.Using Lyapunov stability analysis,uniform boundedness of the MIMO nonlinear control system is proved,and simulation results for a certain type of turbofan engine further validate the effectiveness and performance of the proposed control method. |
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| Keywords: | aero-engine backstepping robustness adaptive neural networks |
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