它通过构造伪输出辨识被控对象参数，引进反馈误差，实现对解耦神经网络的在线训练。
It can identify the parameters of a controlled object by forming a fake output and bring in a feedback error for performing an on-line training to decouple the neural network.
针对输入和输出均为时变函数或过程的实际系统建模和仿真问题，提出一种输入和输出均为时变函数的反馈过程神经网络模型。
In order to model and simulate systems with time-varying functions or processes, a feedback process neural network model with time-varying input and output functions is proposed.
利用人工神经网络，讨论了线性定常控制系统关于状态反馈、输出反馈及动态补偿器的极点配置问题。
By Using an artificial neural network, the pole assignment problem of state feedback, output feedback and dynamic output feedback compensators in linear control system are discussed.
采用非线性反馈控制电流内环，用RBF(径向基函数)神经网络设计了神经网络控制器控制输出电压外环。
Employing a RBF (radical basis function) neural network, a neural network controller is proposed for the output voltage control of the Buck - Boost converter.
然后，针对输入—输出反馈线性化得到的数学模型中的非线性项，本文利用神经网络来对该部分进行逼近。
Then a neural network is employed to approximate the non-linear component of the input-output linearized system.
然后，针对输入—输出反馈线性化得到的数学模型中的非线性项，本文利用神经网络来对该部分进行逼近。
Then a neural network is employed to approximate the non-linear component of the input-output linearized system.
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