同时指出，利用神经网络不仅可以对系统的状态进行辨识，而且可以辨识其相对阶数，并给出了完整的证明。
In the meantime, it is proved strictly that not only the system states but also the relative degree can be identified by using the neural network.
计算量采用修正标量位，这样在同样的节点数下相对于矢量位它可以减少联立方程的阶数。
The modified scalar potential is used to reduce the order of the coupled equations in the comparison with the vector potential under the same node number.
针对一类系统相对阶小于系统阶数的非线性系统，提出了一种基于输入输出线性化的观测器设计方法。
An observer design approach based on input-output linearization for a class of nonlinear systems whose relative degree is less than its orders is proposed.
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