带神经网络辨识器的鲁棒控制器设计。
最后通过神经网络辨识，得到了较为满意的结果。
Ultimately, by using Artificial Neural Network (ANN) method, satisfactory identification result was obtained compared with the …
系统辨识采用了最小二乘辨识和神经网络辨识两种方法。
Two kinds of methods of system identification which are least squares identification and neural network identification are adopted here.
在神经网络辨识的基础上，提出一种新的鲁棒迭代学习控制方法。
Using identification of neural networks, a new method of robust iterative learning control algorithm is proposed in the paper.
提出了一种利用小波神经网络辨识非线性系统多模型故障的方法。
The method for the multiple model failure detection is presented based on wavelet neural network and the designed neural network observer to increase the precision of the identification.
与传统非线性辨识方法不同的是，神经网络辨识不受非线性模型的限制。
Different from the traditional nonlinear identification method, NNI is not restricted by the nonlinear model.
将神经网络辨识技术应用于船舶运动控制成为近年来研究的一个重要方向。
The application of neural network identification techniques in ship control became an important research area in recent years.
理论证明，只要神经网络辨识模型的精度足够高，就会获得很好的控制精度。
It is proved that the control performance is very well under the enough accuracy of the identification model.
介绍了在批量处理时间序列情况下，BP神经网络辨识预测电力负荷的方法和步骤。
The method and steps of BP (Back Propagation) neural network for recognizing and forecasting power load in batch data processing of chronological sequence is presented.
仿真结果表明采用RBF神经网络辨识建模的方法是有效的，建立的模型精度较高。
Simulation results indicate that the modeling method by using the RBF neural network identification technique is effective with the established model featuring a relative high precision.
提出了一种带模糊补偿的神经网络辨识器，并应用在某型涡扇发动机转速控制系统中。
A new neural network algorithm with fuzzy logic compensation was proposed and applied to an aero-engine rotating speed control system.
应用仿真对建模的有效性和精度进行了检验，并与BP神经网络辨识的效果进行了对比。
The validity and accuracy of modeling are tested by simulations, and the simulation results of the comparison between RBF neural networks and BP neural networks identification are given.
针对不确定非线性混沌系统，提出了一种基于动态神经网络辨识器的自适应跟踪控制新方法。
An adaptive tracking controller based on dynamical neural network identifier for uncertain nonlinear chaos systems is presented.
结果表明，用r BF神经网络辨识发动机起动模型，具有方法简单、学习速度快、辨识精度较高等优点。
The results show that this start model features simple procedure, quick to learn and precision when use RBF neural networks for engine model identification.
针对单输入单输出非线性系统的自适应控制问题，提出了一种在线自适应模糊神经网络辨识与鲁棒控制的方法。
An online adaptive fuzzy neural network identification and robust control approach were proposed for the adaptive control problem of SISO 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.
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.
针对异步电动机直接转矩控制系统，基于三相异步电机方程提出一种新型的采用人工神经网络辨识电机转速的方法。
The paper presents a novel speed identification scheme based on the BP Neural Network for the DTC motor drive system.
将神经网络辨识、遗传算法全局优化和预测控制思想有机结合，提出了一种新型控制器，用于带约束的非线性对象的控制。
A constrained nonlinear control algorithm is proposed which combining neural networks identifying, GA optimizing and the idea of predictive control.
针对现有的熔融碳酸盐燃料电池(MCFC)模型过于复杂的弊端，本文应用rbf神经网络辨识方法建立了MCFC的温度非线性模型。
According to the drawback of the models existed which are too complicated, we set up a nonlinear temperature model of MCFC using RBF neural networks identification technology.
本文研究了电子和电路系统存在的混沌现象的神经网络控制问题，其中包括两个方面的内容：混沌系统的神经网络辨识技术和基于神经网络的混沌控制。
In this paper, research concentrates on the neural network control of chaotic systems in electronics and circuits systems, including two fields: chaotic systems identification and chaotic control.
讨论了利用仅含一个隐层的前馈多层神经网络来辨识离散时间非线性动态系统时的模型检验问题。
This paper investigates the problem of the model validation in identifying discrete-time-nonlinear dynamic systems by using neural networks with a single hidden layer.
将这些特征量作为神经网络的输入可以实现电能质量的辨识。
And these eigenvalues can be used as the input vectors of the artificial neural network to classify the power quality signals effectively.
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。
To test the dynamic property, this pneumatic fatigue test system was identified by a recursive BP neural network.
采用简化迟滞算子对模型进行预处理后，构造神经网络实现模型的辨识。
Then a neural network was built to identify the new model based on simplified hysteresis operators.
分析了动态递归神经网络系统辨识的参数学习算法。
The parameter learning algorithm of dynamic recurrent neural network based on system identification is analyzed. D.
与改进BP算法相结合，各取所长，形成集成化动态递归神经网络建模辨识算法。
The identification algorithm integrating the forward evolutionary algorithm and improved BP algorithm for the dynamic recursive neural network model is formed.
该文提出一种用于复杂的非线性未知系统辨识的混合神经网络模型—自适应模糊神经网络(AFNN)。
This paper presents a compound neural network model, i. e., adaptive fuzzy neural network (AFNN), which can be used for identifying the complicated nonlinear system.
根据电液伺服系统的故障特点，本文提出了采用模糊神经网络做在线辨识器的容错控制方案。
According to fault characteristic of the electro hydraulic servo system, this paper has proposed a fault tolerant project that USES the fuzzy neural network as an identifier on-line.
根据电液伺服系统的故障特点，本文提出了采用模糊神经网络做在线辨识器的容错控制方案。
According to fault characteristic of the electro hydraulic servo system, this paper has proposed a fault tolerant project that USES the fuzzy neural network as an identifier on-line.
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