基于自适应噪声对消技术及人工神经网络(ANN)理论，提出了一种谐波电流动态检测方法。
Based on self adaptive noise countervailing method and artificial neural network (ANN) theory, this paper proposes a new approach to the dynamic detecting harmonics.
根据反馈线性化理论，讨论了神经网络自适应非线性动态逆控制设计。
A discussion is devoted to the design of a self adaptive and nonlinear dynamic neural network inversion controller according to the feedback linearization theory.
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.
基于神经网络动态逆方法，给出了一种非线性模型参考自适应跟踪控制方案。
A plan of model reference adaptive tracking control for nonlinear systems is introduced based on neural network dynamic inversion (NNDI).
数字地球是一个复杂、动态变化的自适应网络系统。
Digital Earth is an adaptive network system which has characteristics of complexity and dynamic change.
针对BP神经网络的缺点，研究了一种动态自适应调整学习参数的改进型BP算法。
To BP neural shortcoming of network, study one dynamic self-adaptation is it study improvement type BP algorithm of parameter to adjust.
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。
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.
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.
并在分析了系统误差的基础上，用一个自适应动态神经网络补偿系统的近似逆误差和前向神经网络的映射误差。
According to analyzing the errors of the system, one adaptive neural networks are used to compensate the error of simplified system and the mapping error of feed-forward neural networks.
研究了一类采样数据非线性系统的动态神经网络稳定自适应控制方法。
A stable adaptive control approach using dynamic neural networks has been developed for a class of multi input multi output MIMO sampled data nonlinear systems with unknown dynamic nonlinearities.
该MNN网络能用于在线学习对象的动态特性，从而提供一种能提高整个控制系统性能的自适应控制实现策略。
The MNN can be used for on -line learning of the plant's dynamic characteristics and provide a kind of adaptive control strategy which can improve the whole control system's performance.
采用RBF神经网络逼近系统未知的非线性函数，引入滑模误差对其权值进行在线自适应调整，改善动态性能。
RBF neural network is proposed to approximate unknown nonlinear function. Sliding mode error is used to adaptively tune its weights online. Dynamics performance is improved.
研究了简化型内回归神经网络基于自适应梯度下降法的训练算法，并提出了一种基于简化型内回归神经网络的非线性动态数据校核新方法。
An adaptive gradient descent algorithm for training simplified internally recurrent networks (SIRN) is developed and a new method of reconciling nonlinear dynamic data based on SIRN is proposed.
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.
接着，结合其存在的问题，对动态递归神经网络、R BF神经网络和自适应逆控制进行了算法研究。
Then, aiming at the existing problem, the algorithm of dynamic recurrent neural network, RBF neural network and adaptive inverse control is studied in the paper.
针对一类非线性动态系统，提出了一种新的基于多层神经网络的自适应预测器，并对基于神经网络的预测机理进行了分析。
This paper develops a novel multilayer neural networks based on adaptive prediction technique for a class of nonlinear dynamical systems, and the prediction mechanism is analyzed .
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.
仿真实验结果表明，具有自适应神经网络的模糊推理系统控制的异步电机矢量控制系统不仅动态和稳态性能都得到提高，而且具有较强的鲁棒性。
Simulation results show that the induction motor vector control system with adaptive neuro-fuzzy inference system can improve the static and dynamic performance of the motor and has good robust.
针对航天器姿态系统，提出了一种基于自适应神经网络动态逆的控制算法。
To study the attitude system of spacecraft, an adaptive inverse control algorithm is presented.
自适应动态滑动模控制的作用有两个：其一是在神经网络控制失灵的情形下提供控制系统的全局稳定性；其二是改善系统的跟随性能。
The dynamic sliding mode control serves two purposes, one is to provide the global stability of the closed loop system, and the other is to improve the tracking performance.
针对一类不确定的离散时间非线性非最小相位动态系统，提出了一种基于神经网络和多模型的直接自适应控制方法。
A direct adaptive control approach is proposed for a class of uncertain discrete time nonlinear non-minimum phase dynamical systems.
提出了一种自适应负载动态变化的无线传感器网络MAC协议。
This paper proposes an adaptive dynamic load MAC protocol for wireless sensor network.
提出了一种新的基于网络丢包率的动态自适应的主动队列管理的改进算法。
A new dynamic adaptive AQM (Active Queue Management) scheme based on network loss ratio is proposed.
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.
其目的是通过本课题的研究，进一步提高无线自组网的动态自适应能力，完善其网络层提供的路由服务，并通过不同协议之间的分析和对比，寻找最优的性能。
And developed a routing protocol based on this infrastructure. The purpose is to improve the dynamic adaptability, the routing service and to find the best performance by the research.
本文针对一类非线性动态系统，提出了一种新的基于后向回归网络的自适应多步预测方法，并对基于神经网络的自适应预测机理进行了分析。
This paper develops a novel backpropagation networks based adaptive multistep prediction technique for a class of nonlinear dynamical systems, and the prediction mechanism is analyzed.
讨论了一种基于神经网络动态逆的直接自适应控制方法，并应用于超机动飞机的飞行控制中。
An adaptive controller with a neural network compensator is designed and applied in the control of a super-maneuvering aircraft.
讨论了一种基于神经网络动态逆的直接自适应控制方法，并应用于超机动飞机的飞行控制中。
An adaptive controller with a neural network compensator is designed and applied in the control of a super-maneuvering aircraft.
应用推荐