该方法结合了神经网络和逆系统控制的优点，能够克服系统中的不确定性和非线性因素。
The proposed controller combines the advantages of neural network and inverse system control, and can compensate the influence of uncertainty and nonlinearity.
利用动态逆方法设计了快子系统控制律。
The slow subsystem control law is designed by Lyapunov method.
文章对此提出采用模型参考逆方法控制方案，该控制方案兼有模型自适应控制及逆系统控制等方案的特点，且具有很强的抗干扰能力。
In this paper, the model reference and inverse method which has the advantage of model self-adapted control and inverse system control and has strong anti-disturbance function was presented.
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