利用模糊控制在线自适应调整PID控制器的参数，从而使系统的静态和动态性能指标较为理想。
Fuzzy control is used to adjust the parameters of PID control on-line, accordingly it can make static and dynamic performance index comparatively ideal.
利用对角递归神经网络在线自适应调整PID控制器的参数，从而使系统的静态和动态性能指标较为理想。
DRNN is used to adjust the parameters of PID control on-line, accordingly it can make static and dynamic performance index comparatively ideal.
采用RBF神经网络逼近系统未知的非线性函数，引入滑模误差对其权值进行在线自适应调整，改善动态性能。
RBF neural network is proposed to approximate unknown nonlinear function. Sliding mode error is used to adaptively tune its weights online. Dynamics performance is improved.
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