提出了一种基于T - S模糊模型和自适应神经网络的跟踪控制方法。
A robust adaptive tracking control method is presented based on the fuzzy T-S model.
自适应神经网络模型对于葡萄病害发生程度的预侧具有重要的参考价值。
So the model of the prediction of grape disease based on adaptive neural networks has the important reference value.
采用自适应神经网络控制方法，设计出倾转旋翼机模拟平台姿态角控制器。
An adaptive neural networks controller is designed for tilt rotor aircraft platform.
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.
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.
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.
基于数据融合的思想，提出一种非线性系统的自适应神经网络模糊控制器的设计方法。
Based on data fusion method, an adaptive neuro-fuzzy controller of nonlinear systems is presented.
并以麻醉剂模式对这种自适应神经网络的成立条件进行推导，对其稳定性进行了验证。
In the anesthetic mode, the conditions of the loop mode is deduced and the stability of it is validated.
本文首先在对现有几种谐波检测方法总结对比的基础上，研究了基于线性自适应神经网络的谐波检测方法。
Above all, the harmonics detecting method of adaptive linear neural network is studied in this paper after compared a few harmonics detecting methods in existence.
提出一种新型的过热汽温控制方案，主控制器基于自适应神经网络模糊推理系统(ANFIS)进行设计。
A new superheated steam temperature control system design scheme is proposed, the main controller design is based on Adaptive Network-based Fuzzy Inference system (ANFIS).
该文应用自适应神经网络模糊推理系统的方法对一个典型系统进行建模仿真，并阐述这三个参数的寻优方法。
This paper gives the simulation example for modeling a typical system with Adaptive Neural-Fuzzy Inference system and expatiates the method for choosing these three parameters.
通过一个非线性实例设计了它的自适应神经网络模糊模型，从仿真结果可看出改进后的非线性系统模型更有效。
By designing a self-adapt neural fuzzy model for a nonlinear system, we can draw a conclusion that the new nonlinear model has high precision and good visual effect.
借助于辨识的过量空气系数自适应神经网络模糊推理系统(ANFIS)模型，进行了静态空燃比前馈控制仿真。
By means of an identified adaptive neural fuzzy inference system (ANFIS) model of the excess air factor, the simulation of static state air fuel ratio feed-forward control was carried out.
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.
在某些部件部分意外失效或战损情况下，自适应神经网络具有实现控制的在线快速重新配置、保持飞行品质的潜力；
The adaptive neural network has a potential ability of PCS redesign and maintenance of handling quality, following unexpected part failures and battle damage.
自适应神经网络模糊推理系统(ANFIS)能基于数据建模，无须专家经验，自动产生模糊规则和调整隶属度函数。
Applying Adaptive Neural-Fuzzy Inference System (ANFIS) can produce fuzzy rules and adjust membership functions automatically based on data without experience of experts.
当获得了足够的数据后，通过自适应神经网络模糊系统ANFIS来训练产生隶属度函数和模糊规则，即产生模糊控制器。
When obtaining plenty data, self-adapt neural network fuzzy control system ANFIS come into being subjection degree function and fuzzy rule, namely come into being fuzzy controller.
本文首先引入一个能方便进行在线自适应的扩展控制对象自适应神经网络模型，在此基础上提出一种噪声有源控制的自适应神经网络方法。
This paper firstly introduces an extended plant adaptive neural network model which can be on-line adapted conveniently, then presents a method of active noise control using adaptive neural networks.
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.
本文还详细介绍了一种用多层前向神经网络实现模糊逻辑的自适应神经网络模糊推理系统——ANFIS，并用它来分析、验证神经模糊控制的控制效果。
This paper also stated the method of Adaptive Neural-Fuzzy Inference System (ANFIS) in details, which was used to analysis and testify effect of the NN-FC.
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.
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.
本文根据变量泵的具体情况，为其设计了自适应的神经网络模糊控制器，实现了变量泵的智能控制。
This paper describes that the combination of neural networks and fuzzy controller make the designing an intelligent controller for variable piston pumps become feasible and realistic.
本文提出了一种基于改进的神经网络(MNN)的自适应闭环功率控制算法，该方法平滑了移动信道衰落的影响，使基站接收到的小区中所有用户的信号功率相等。
In this paper, a Modified Neural Network (MNN) based power controller is proposed to smoothen out the fast fading and keep the received signal power from each user constant at the base station.
本文将自适应线性神经网络理论应用于非线性负载电流中畸变电流的检测。
Adaptive linear neural network is used for detecting the distortion currents of nonlinear loads.
结果表明，相对于常规PD控制器，该神经网络控制器具有自学习、自适应功能，位置跟踪获得了满意的控制效果。
The simulation results prove that the neural network controller has self-learning and self-adaptive ability by comparison with PD controller. The position tracking control obtains satisfactory effect.
该文根据生物神经元状态变化导致人脑空间结构和状态变化这一原理，提出了一种自适应构造神经网络的新方法。
According to the principle of biological neuron, which state influences the condition of the brain, a new method is presented to adaptively construct neural networks.
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.
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.
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