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Description: 基于RBF的PID控制matlab程序，望大家参考，共同学习。-PID control based on RBF
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Size: 1024 |
Author: 康 |
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Description: 针对实际对象数学模型不明确而难以控制的问题,采用人工免疫网络的离散模
型与学习算法,将人工免疫系统与神经网络结构的优势相结合,提出了一种基于人工免疫
网络的模式识别算法,构造了对象识别的人工免疫网络模型.该算法综合了网络节点的定
位与参数调整以及对基函数的平滑因子实施调谐等功能,有效地解决了径向基函数
(RBF)神经网络模式识别的两个阶段任务,使模式识别的精度有较大的改进.采用两个不
同对象函数进行的仿真试验表明,该算法具有快速收敛性与较高的准确性.
-Mathematical model for the actual object is not clear and difficult to control the problem, the use of artificial immune network model and the discrete learning algorithm, artificial immune systems and neural networks combine the advantages of structure, an artificial immune network based on pattern recognition algorithms, Construction of the object identified by artificial immune network model. the algorithm is a combination of network nodes to adjust the position and parameters as well as the basis function implementation of the smoothing factor, tuning and other functions, to effectively solve the Radial Basis Function (RBF) neural network pattern recognition of two phase of the task, so that the accuracy of pattern recognition have greater improvements. the use of two different object functions of the simulation tests show that the algorithm has fast convergence and higher accuracy.
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Size: 114688 |
Author: 杨玉琴 |
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Description: 该PPT提供了无刷电机无位置控制的新方法...RBF神经网络控制...我们积极在这方面做实验，取得了一定的效果-The PPT provides a brushless motor without position control of the new method ... RBF neural network control ... We are actively conducting experiments in this regard, and achieved some results
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Size: 95232 |
Author: gexiaozhong |
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Description: 基于RBF神经网络辨识的单神经元PID模型参考自适应控制-RBF neural network-based identification of single neuron PID model reference adaptive control
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Size: 1024 |
Author: 周凯 |
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Description: 基于模糊RBF网络整定的PID控制,采用增量PID形式-RBF network based on fuzzy tuning of PID control, PID form of incremental
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Size: 1024 |
Author: wutiebing |
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Description: RBF神经网络预测控制，预测控制，RBF神经网络-RBF neural network predictive control, predictive control, RBF neural network
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Size: 19456 |
Author: yuyu |
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Description: 用RBF神经网络算法对非线性干扰进行估计，提高控制精度，并将其与普通滑模控制进行比较。(The RBF neural network algorithm is used to estimate the nonlinear disturbance, and the control accuracy is improved.)
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Size: 32768 |
Author: 疏影清浅
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Description: RBF网络能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性，具有良好的泛化能力，并有很快的学习收敛速度，已成功应用于非线性函数逼近、时间序列分析、数据分类、模式识别、信息处理、图像处理、系统建模、控制和故障诊断等。(RBF network can approximate any nonlinear function, regularity can handle within the system to parse, has good generalization ability and learning, fast convergence speed, and has been successfully applied to nonlinear function approximation, time series analysis, data classification, pattern recognition, information processing, image processing, system modeling, control and fault diagnosis.)
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Size: 5120 |
Author: gahuan
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Description: 基于RBF网络逼近的自适应控制，含有详细内容讲解，仿真实例以及详细的MATLAB代码(RBF network approximation based adaptive control, including detailed explanations, simulation examples, as well as detailed MATLAB code)
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Size: 63488 |
Author: 有恃无恐2L
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Description: 《RBF神经网络自适应控制的matlab仿真》刘金琨著 程序包("RBF neural network adaptive control matlab simulation" Liu Jinkun program package)
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Size: 268288 |
Author: Taurus.0915
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Description: RBF网络能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性，具有良好的泛化能力，并有很快的学习收敛速度，已成功应用于非线性函数逼近、时间序列分析、数据分类、模式识别、信息处理、图像处理、系统建模、控制和故障诊断等。(RBF network can approximate any nonlinear function, regularity can handle within the system to parse, has good generalization ability and learning, fast convergence speed, and has been successfully applied to nonlinear function approximation, time series analysis, data classification, pattern recognition, information processing, image processing, system modeling, control and fault diagnosis.)
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Size: 47104 |
Author: 哼哼1214
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Description: RBF网络的双力臂自适应数字控制设计仿真程序(RBF control for two link manipulators)
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Size: 1024 |
Author: hunterFM |
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Description: 对于模型分块逼近的机器人RBF网络的自适应控制仿真程序(An Adaptive Control Simulation Program of Robot RBF Network for Model Blocking Approximation)
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Size: 2048 |
Author: hunterFM |
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Description: 基于RBF神经网络的控制算法，书籍源代码，非常好用。(Control algorithm based on RBF neural network,Book source code, very useful.)
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Size: 270336 |
Author: gjessing1 |
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Description: RBF神经网络控制设计Matlab仿真程序(ATLAB Simulation Program for RBF Neural Network Control Design)
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Size: 285696 |
Author: xudengguo |
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Description: 基于梯度下降法RBF自适应神经网络控制(RBF adaptive neural network control based on gradient descent method)
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Size: 2048 |
Author: 筱绡 |
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Description: 智能控制例程，MATLAB倒立摆控制程序(Intelligent Control Routines, MATLAB Inverted Pendulum Control Program)
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Size: 44032 |
Author: Unicor |
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Description: RBF网络能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性，具有良好的泛化能力，并有很快的学习收敛速度，已成功应用于非线性函数逼近、时间序列分析、数据分类、模式识别、信息处理、图像处理、系统建模、控制和故障诊断等。
简单说明一下为什么RBF网络学习收敛得比较快。当网络的一个或多个可调参数（权值或阈值）对任何一个输出都有影响时，这样的网络称为全局逼近网络。由于对于每次输入，网络上的每一个权值都要调整，从而导致全局逼近网络的学习速度很慢。BP网络就是一个典型的例子。(RBF network can approximate arbitrary non-linear functions, can deal with the laws that are difficult to analyse in the system, has good generalization ability, and has very fast learning.
The convergence rate has been successfully applied to non-linear function approximation, time series analysis, data classification, pattern recognition, information processing, image processing and system construction.
Modeling, control and fault diagnosis.
Simply explain why RBF network learning converges faster. When one or more adjustable parameters (weights or thresholds) of the network are applied to any output
When there is an impact, such a network is called a global approximation network. For each input, each weight on the network has to be adjusted, which leads to global approximation.
The learning speed of the network is very slow. BP network is a typical example.
If only a few connection weights affect the output for a local area of the input space,)
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Size: 2573312 |
Author: shunzi1999 |
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Description: 刘金琨老师的著作，主要讲RBF在控制方面的应用，章节末附有源程序(Liu Jinkun teacher's work, mainly about the application of RBF in control, chapter end with the active program)
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Size: 51730432 |
Author: 醉里挑灯看雪 |
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Description: RBF神经网络自适应控制MATLAB仿真全书及代码(RBF neural network adaptive control matlab simulation and code)
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Size: 51965952 |
Author: 烟雨雾林 |
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