提出一种对水轮发电机组水压频率进行综合调节的记忆递归网络灵敏度预测控制器。
A sensitivity predictive controller with memory recurrent network for use in the comprehensive control of the water hammer and the frequency is proposed.
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.
基于人工神经网络提出了一种局部递归神经网络控制器。
A locally recurrent neural network controller based on neural network is proposed.
针对仿射非线性系统，提出了一种新型的基于动态递归模糊神经网络(DRFNN)的间接自适应控制器。
A novel indirect adaptive controller based on dynamic recurrent fuzzy neural network (DRFNN) is proposed for affine nonlinear system.
提出一种基于动态递归神经网络的自适应pid控制方案，该控制系统由神经网络辨识器和神经网络控制器组成。
This paper presents an adaptive PID control scheme based on dynamic recurrent neural network. The control system is consisted of the neural network identifier and the neural network controller.
该网络控制器的隐含层由带有输出反馈和激活反馈的混合局部连接递归网络组成。
It is composed of a hybrid locally connected recurrent network with an activation feedback and an output feedback respectively in the hidden layer.
在这种自适应逆控制机制中，逆模型通过递归最小二乘算法更新，控制器依据-滤波进行在线调整。
In this adaptive inverse control mechanism, the inverse model is updated through recursive least squares algorithm, and controller is adjusted online according to method of filter.
提出一种基于动态递归神经网络的自适应pid控制方案，该控制系统由神经网络辨识器和神经网络控制器组成。
An adaptive PID control scheme based on dynamic recurrent neural network is presented. The control system is consisted of the neural network identifier and the neural network controller.
提出一种基于动态递归神经网络的自适应pid控制方案，该控制系统由神经网络辨识器和神经网络控制器组成。
An adaptive PID control scheme based on dynamic recurrent neural network is presented. The control system is consisted of the neural network identifier and the neural network controller.
应用推荐