该模拟神经控制器能用于不确定对象的控制，为不确定系统控制提供了一种新的途径。
The analog neural controller is suitable for the control over uncertain objects and provides a novel approach for a type of uncertain control system.
该模拟神经控制器能用于不确定对象的控制，为不确定系统控制提供了一种新的途径。
The analog neural controller can be applicable to the control of uncertain objects and provides a novel approach for the type of an uncertain control system.
不确定非线性系统控制是目前控制理论研究的一个重要课题。
Uncertain nonlinear systems control is an important topic in control theory.
该方法结合了神经网络和逆系统控制的优点，能够克服系统中的不确定性和非线性因素。
The proposed controller combines the advantages of neural network and inverse system control, and can compensate the influence of uncertainty and nonlinearity.
结果表明，适应性非线性控制器（ANLC）具有很强的适应性能，是解决不确定高阶非线性系统控制的有效途径。
Simulation results compared with exact feedback linearization show that ANLC has good adaptability and it is an effective approach for uncertain high-order nonlinear systems.
电力系统暂态稳定控制问题的难点是要解决一个具有强非线性、不确定性的大系统控制问题。
The difficulty of solving transient stability problem is to deal with the strongly nonlinear, uncertain and large - scale system.
由线性矩阵不等式(LMI)设计系统标称部分的鲁棒控制器，然后利用神经网络的输出来消除系统控制输入中的不确定部分。
The robust controller is designed using linear Matrix Inequality (LMI) for the nominal linear flight system. And then, the uncertain nonlinear input term is compensated using the neural network.
由线性矩阵不等式(LMI)设计系统标称部分的鲁棒控制器，然后利用神经网络的输出来消除系统控制输入中的不确定部分。
The robust controller is designed using linear Matrix Inequality (LMI) for the nominal linear flight system. And then, the uncertain nonlinear input term is compensated using the neural network.
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