提出利用直接自适应模糊神经网络控制一类不确定非线性混沌系统新方法。
A novel direct adaptive fuzzy neural networks (FNNs) controller for a class of uncertain nonlinear chaotic system is presented.
其主要特点是能够提供一个跟踪网络来辩识系统模型，进而确定控制器的网络参数，实现间接自适应神经网络控制。
Its major feature is that it can provide a tracing network to identify system model so as to determine the network parameters of the controller and realize an indirect adaptive neural network control.
当前神经网络的主要应用领域有：模式识别、自适应控制、市场分析、决策优化、预测分析、知识处理等。
Present applications of neural network are as follows: pattern-recognition, self-adaptation control, market analysis, decision optimization, prediction analysis, knowledge processing, etc.
第二种方法则是基于误差通道在线辨识的神经网络自适应控制方法。
The second method is the adaptive control by using neural networks based on online secondary path modeling.
提出一种新的基于神经网络的机器人模型参考自适应控制方法。
A new robot model reference adaptive control method based on neural networks is presented.
基于递归神经网络给出了仅含一个非线性环节的一类非线性系统的自适应控制方案。
A scheme of adaptive control based on recurrent neural network is presented for a class of nonlinear systems only with a nonlinear part.
在此基础上，又设计了模糊神经网络预测控制器，实现了对非线性、大时滞系统高精度的自适应控制。
On the basis of this, a fuzzy-neural forecast controller is designed and robust adaptive control to the nonlinear big-lagged chaos system is realized.
文章针对一类非线性系统，研究了一种基于回馈递推法的自适应神经网络控制方法。
An adaptive back stepping control method based on neural networks is presented for a class of nonlinear systems.
前馈神经网络由于具有理论上逼近任意非线性连续映射的能力，因而非常适合于非线性系统建模及构成自适应控制。
Because the feedforward neural network has an ability of approach to arbitrary nonlinear mapping, it can be used effectively in the modeling and controlling of nonlinear system.
提出一种基于遗传算法的神经网络非线性自适应控制方案。
This paper presents a kind of adaptive neural network nonlinear systems control method based on genetic algorithms.
在反馈学习算法的基础上，将模糊逻辑和神经网络自适应控制的结构结合在一起。
The neural network-based adaptive control and fuzzy logic are integrated based on feedback learning algorithm.
提出一种改进的模型跟随自适应控制算法，该改进算法把系统当前输出误差引入控制信号，同时利用线性神经网络估计系统新的输出误差。
A modified adaptive model following control algorithm was presented, in which the system output error is added to control signal and the next time output error is evaluated by linear networks.
各控制子系统的设计采用自适应控制和神经网络相结合的方法，所提出的参数和权重的自适应调整律保证系统的稳定性。
Each subsystem is designed using adaptive control with neural network compensation. The stability of the system is guaranteed by the proposed parameter and weight turning law.
针对混沌系统的控制问题，提出了一种基于神经气网络的模糊多模型自适应控制方法。
Aiming at chaotic system, this paper proposes a multi-model adaptive control strategy based on a neural-gas network with fuzzy logic.
首先根据模型参考自适应控制理论，将模型逆与在线神经网络结合，设计了神经网络自适应姿态控制系统。
The neural network adaptive attitude control system is designed based on model reference adaptive control theory and combination of online neural network with augmented model inversion.
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.
文章在已有的网络安全功能模块基础上，应用自适应控制与调节原理重构自适应的网络安全部件。
Based on the existing network security module, in this paper, the model of the self adaptation security com-ponents are reconstructed by applying the principle of auto-adapted adjustment.
提出一种利用神经网络的自学习特性，对陀螺稳定平台的速度环进行自适应控制的方法。
Based on the self-learning property of neural network, an adaptive control method for speed ring of a gyroscope-stabilized platform is put forward in the paper.
研究了一类具有未知常数控制增益的耦合大系统的直接自适应神经网络控制问题。
The problem of direct adaptive neural network control for a class of interconnected systems with unknown constant control gains is studied in this paper.
本文根据模型参考自适应控制理论，将旋转动力学逆与在线神经网络结合，设计了自适应姿态控制系统。
An adaptive neural network attitude control system is designed based on model reference adaptive control theory and combination of online neural network with augmented model inversion in this paper.
本文研究神经网络自适应控制方法及其在航空发动机控制中应用。
A new neural network adaptive control scheme is presented and its applications to aero-engine control system are researched.
为提高PID控制的自适应性能，提出了一种神经网络PID自适应控制算法。
A neural network PID control algorithm is presented to improve the PID adaptive control performance.
针对工业过程的特点和控制要求，提出一种基于多步预测的神经网络自适应控制算法。
Adaptively controlling algorithm based on neural network of multi-step prediction was proposed for the industrial processes.
第一种方法一是基于误差通道离线辨识的神经网络自适应控制方法。
The first method is the adaptive control by using neural networks based on offline secondary path modeling.
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.
针对悬架系统的辨识和控制过程，本文提出一种神经网络间接自适应控制方法，优化了控制结构，提高了控制精度。
And it proposes an indirect adaptive neural network law. This law optimizes the control structure and improves the quality of control.
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.
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.
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