针对两种典型的非线性奇异摄动系统，文中分别给出了状态反馈校正法和状态前馈校正法。
For two typical nonlinear singularly perturbed systems, we give one state feedback corrected control and one state forefeed corrected control respectively.
利用广义系统模型，通过改进已有的广义系统正实引理，讨论了奇异摄动系统的正实性判断问题。
To discuss the strictly positive realness judgment criteria of singularly perturbed systems, a singular system model is employed, and the existing positive real lemma of singular systems is improved.
将改进的概率神经网络(PNN)用于奇异摄动系统的实时状态估计，注重针对系统快变部分的滤波。
Probabilistic Neural Networks (PNN) is improved and used on line to estimate the states of singular perturbed systems, especially to the fast states of the systems.
将改进的概率神经网络(PNN)用于奇异摄动系统的实时状态估计，注重针对系统快变部分的滤波。
Probabilistic Neural Networks (PNN) is improved and used on line to estimate the states of singular perturbed systems, especially to the fast states of the systems.
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