本文主要将自适应控制、变结构控制与神经网络相结合，提出性能更优越的神经网络自适应变结构控制。
In this paper, adaptive control, sliding mode variable structure control and neural network are combined, a superior neural network adaptive variable structure control is introduced.
所提出的近似自适应变结构控制器可以避免控制器中的不连续继电项，同时不必已知系统不确定性范数界。
Then, the normal variable structure controller (VSC) and the adaptive variable structure controller with the estimation for the upper norms of uncertainties are presented.
作为现代控制领域中的一个重要分支，基于模糊建模的非线性系统的鲁棒自适应变结构控制技术近年来受到了国内外控制界的广泛重视。
As an important branch in the field of intelligent control, fuzzy model based robust adaptive sliding-mode control for nonlinear systems has received more and more attention in recent years.
采用饱和型标量函数构成非线性滑模建立直流伺服机器人控制系统的自适应变结构数学模型。
Mathematical model of adaptive variable structure of control system for DC servo robot was established with nonlinear sliding mode formed with saturation type scalar functions.
采用饱和型标量函数构成非线性滑模建立直流伺服机器人控制系统的自适应变结构数学模型。
Mathematical model of adaptive variable structure of control system for DC servo robot was established with nonlinear sliding mode formed with saturation type scalar functions.
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