主要阐述了用输入—状态线性化来消除分岔的非线性控制方法，使得当参变量无论怎样变化，系统始终都能保持在渐进稳定的平衡态。
It's illustrated how Input state linearization method is used to eliminate bifurcation so that no matter how the parameters change the system could maintain asymptotic stable equilibrium state.
随着输入项的变化，混沌神经元状态有规律的在混沌态和周期态之间相互转化，利用这种特性可以控制混沌神经元的内部状态。
As the input item varying, chaotic neuron status transforms between chaos and periods, which should be used to control the interior status of chaotic neuron.
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