In this paper, a new multivariable self-tuning feedforward controller is presented.
本文提出了一种新的多变量自校正前馈控制器。
The unstable zeros of a non minimum phase system are difficult problems for feedforward controller design.
系统的不稳定零点给前馈控制器的设计带来了很大的困难。
In feedforward, based on the neural network control theory, a feedforward controller is designed for disturbances overcoming of the control system.
在前馈部分，构造了一种基于神经网络的前馈控制器，用于主汽温系统的干扰抑制。
An improvement which adds fuzzy speed feedforward controller to the system is described after analyzing the output curve of rotor speed. Remarkably, the stability of system is enhanced.
并通过分析转速输出曲线，提出了加入模糊速度前馈控制环的系统改进方案，系统稳定性得到较大提高。
The analog compound orthogonal neural network was obtained by means of a continuous algorithm treatment for a digital compound orthogonal neural network, and was used as the feedforward controller.
通过数字复合正交神经网络的连续化算法处理获得了一种模拟复合正交神经网络，并作为前馈控制器。
The analog compound orthogonal neural network was obtained by means of a continuous algorithm treatment for a digital compound orthogonal neural network, and was used as the feedforward controller.
通过数字复合正交神经网络的连续化算法处理获得了一种模拟复合正交神经网络，并作为前馈控制器。
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