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.
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。
A kind of mixture control system, based on dynamic neural network, is designed through analyzing the influence precision factors of mixture.
通过对影响配料精度因素的分析，设计了一种基于动态神经网络的配料控制系统。
With the feedback behavior, the recurrent neural network can catch up with the dynamic response of the system.
由于其反馈特征，使得递归神经网络模型能获取系统的动态响应特性。
With the feedback behavior, the recursive neural network can catch up with the dynamic response of the system.
由于其反馈特征，使得递归神经网络模型能获取系统的动态响应。
Based on this system, a dynamic neural network is used to track the change of quality characteristics during manufacturing process. Numerical simulation and practical experiment show good results.
根据提出的系统模型利用动态神经网络对加工过程质量特征参数的变化进行了跟踪实验，效果良好。
Aiming at problematic complexity of the nonlinear dynamic mathematical modeling of generator in the hydro-electric simulation system, a neural network based on information fusion is brought forward.
文章针对水电仿真系统中水轮发电机机组的非线性动态数学模型建模复杂问题，提出了一种基于信息融合思想的神经网络模型。
To test the dynamic property, this pneumatic fatigue test system was identified by a recursive BP neural network.
为了考察该系统的动态性能，采用递归BP神经网络对该系统进行辨识。
Diagonal recurrent neural network (DRNN) is a modified model of the fully connected recurrent neural network with the advantage in capturing the dynamic behavior of a system.
对角循环神经网络是一类经过修正的全连接循环神经网络，在系统动态行为的俘获方面具有明显的优势。
The parameter learning algorithm of dynamic recurrent neural network based on system identification is analyzed. D.
分析了动态递归神经网络系统辨识的参数学习算法。
The first network is BP network with one hidden layer, and the second network is linear status Neural network based on linear system dynamic equation.
第一种神经网络是具有一个隐层的动态前向BP网络，第二种是基于线性系统动态方程的线性状态神经网络。
Neural network is a kind of highly complex nonlinear dynamic system, and chaotic phenomenon was found in it.
神经网络是高度复杂的非线性动力系统，存在着混沌现象。
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.
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。
A new method was represented to model dynamic linear regression system driven by data, in which a bayesian network was combined with the RBF neural network.
结合贝叶斯网络和神经网络，提出了一种建立数据驱动型的动态线性回归系统模型的方法。
A novel neural network model, named delayed standard neural network model (DSNNM), is proposed, which is the interconnection of a linear dynamic system and a bounded static delayed nonlinear operator.
提出一种新的神经网络模型—时滞标准神经网络模型(DSNNM)，它由线性动力学系统和有界静态时滞非线性算子连接而成。
A novel indirect adaptive controller based on dynamic recurrent fuzzy neural network (DRFNN) is proposed for affine nonlinear system.
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。
Combining it with the adaptive linear neuron network, the multiplex control strategy takes the dynamic errors and given signals of the system as input signals to the CMAC neural network.
该控制器以系统动态误差和给定信号量作为CMAC的激励信号，并与自适应线性神经元网络相结合构成系统的复合控制。
The coordinated control system has dynamic characteristic of nonlinear, varying parameter. Utilizing nonlinear mapping-capability of neural network solves these problems well.
利用神经网络的非线性映射能力，能很好地解决负荷协调控制对象的动态特性具有非线性、时变性、参数可变等问题。
The dynamic recurrent neural network is analyzed, and how to use it for system identification is also analyzed.
对所提出的动态递归神经网络进行了分析，以及如何利用它们来进行系统辨识。
The parameter learning algorithm of dynamic recurrent neural network based on system identification is analyzed.
分析了动态递归神经网络系统辨识的参数学习算法。
The dynamic model of a simulator of the boiler-turbine system of a 375 MW(megawatt) thermal power plant is built by a feedforward neural network that is trained offline.
针对一个375MW热电厂的锅炉—汽轮机系统仿真模型，采用多层前向神经网络进行离线建模；
The neural network, which is a nonlinear dynamic system, has been successfully applied in the channel equalization of binary digital communication systems.
神经网络是一种非线性动力学系统，在二进制系统信道均衡实现方面得到非常成功的应用。
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。
Moreover, T-S model is used to adjust the dynamic fuzzy rules by the latter neural network, which can improve the adaptability of the control system.
采用T - S模型，由后件网络动态调整模糊规则，提高控制系统的适应性。
A compound approach with a set of improved robust observers on fault diagnosis on nonlinear system, with a dynamic neural network deciding parameters, is illustrated with an instance of 3-tank model.
该方法将一组改进的鲁棒观测器与一个为其确定参数的动态神经网络相结合，对非线性系统进行故障诊断。
In view of the disadvantages of zero-pole matching dynamic compensation method, the dynamic compensation method of tilting train measurement system based on non-linear neural network is put forward.
针对零极点匹配动态补偿方法的不足，提出基于非线性神经网络的摆式列车检测系统动态补偿方法。
In the paper, a research on neural network used in train track dynamic system is presented.
本文中研究了神经网络在列车轨道动力学中的应用。
So artificial neural network is a dynamic system with highly non-lineal continued time.
因此神经网络是一种具有高度非线性的超大规模连续时间动力学系统。
The system identifier based on RBF neural network which applies nearest neighbor clustering algorithm realizes the identification of the inverse dynamic system model.
辨识器采用RBF神经网络结构和最近邻聚类算法，实现了对系统逆动力学模型的动态辨识。
The central content of this thesis includes identifying and revising the critical rotate speed-dynamic parameters of rotor-bearing system by the artificial neural network theory and harmonic wavelet.
本论文的核心内容是：应用谐波小波和人工神经网络理论对转子轴承系统动力参数——临界转速进行识别与修正。
The central content of this thesis includes identifying and revising the critical rotate speed-dynamic parameters of rotor-bearing system by the artificial neural network theory and harmonic wavelet.
本论文的核心内容是：应用谐波小波和人工神经网络理论对转子轴承系统动力参数——临界转速进行识别与修正。
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