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参考源码（模糊控制）
- 基于模糊控制的机器人避障，智能控制基础大四。(Obstacle avoidance of fuzzy control robot)
Desktop
- MATLAB模糊函数和脉冲串波形研究，描写了脉冲串波形的主要研究成果已经一个仿真代码(Research on MATLAB fuzzy function and pulse string waveform)
fuzzy_pid
- matlab的模糊工具箱的模糊pid，可直接在matlab模糊控制工具箱打开，直接运行(this file is fis file , the file is a fuzzy controller. you can modificate the parameters.)
SPEEDFUZZY
- This file shows speed control of motor based on fuzzy control
servo-motor
- This file shows servo control based on fuzzy system.
程序
- 根据所学过的BP网络设计及改进方案设计实现模糊控制规则为T = int((e+ec)/2)的模糊神经网络控制器，其中输入变量e和ec的变化范围分别是：e = int[-2, 2]，ec = int[-2, 2]。网络设计的目标误差为 0.001。(According to the BP network design and improvement plan that we have learned, we design a fuzzy neural network controller with
Fuzzy_Controller
- fuzzy logic controller is simulated in matlab simulink.
fuzzy toolbox in matlab
- Try to draw the Simulink plot as the following reference and show the waveforms of
dat file
- fuzzy test file *.rar type
FuzzyTYPE-2
- fuzzy type one using matlab
NLRetinex
- nlretinex using matlab
FuzzyClusteringToolbox_m
- matlab模糊聚类工具箱，包括示例程序 ，工具箱简介PDF文件等。(Matlab fuzzy clustering tool kit, including sample program, toolbox introduction PDF file, etc)
fuzzyfilter
- This paper presents a fuzzy logic algorithm to control DC-bus voltage of a shunt active power filter (APF). This work is done to illustrate the Performance and robustness of current Identification references by calculating the harmonics (THD) res
FuzzyAdrc
- 在自抗扰的基础上，增加了模糊控制，通过经验积累，设置模糊pid控制器，使得控制效果更加明显(On the basis of self disturbance rejection, the fuzzy control is added, and the fuzzy PID controller is set up through experience accumulation, which makes the control effect more obvious.)
模糊控制
- 在MATLAB中，经常运用模糊控制进行PID的控制(In MATLAB, fuzzy control is often used to control PID)
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- this file is contains matlab code for fuzzy network and neural network
ANFIS algorithm
- 自适应神经模糊推理系统的可运行实例，注释清楚易懂(Operable examples of adaptive neuro-fuzzy inference system)
graph cut sigmintation
- Matlab code for fuzzy clustering
work
- matlab补偿模糊神经网络源代码 本文中有两个函数m文件：model126.m是一个用于预测的完全没有用工具箱函数的补偿模糊神经网络主程序，用于仿真、对比训练数据和网络输出的差异；cb.m是一个非线性系统的数学模型，在model126.m中用“ode45”函数求解这个数学模型后，可以得到105个x1(t)、x2(t)和y(t)，从而建立起一个两输入一输出的补偿模糊神经网络。(There are two function m file in this paper: model126.m is
Untitled
- 控制器采用二维的模糊控制器，其输入信号偏差为e和偏差的变化为的de，控制对象为时滞对象： ，假设系统给定为阶跃值R=10，系统的初始值R(0)=0。本例采用的是增量控制方法，所以模糊控制器的其输出量为△U。后面经过一个积分环节，就得到了一个控制信号U。E、dE、△U的模糊论域划分为13个档次，论域取为[-10,10]之间。各个论域E, EC和△U的语言变量为{NB， NS，0，PS，PB}。采用两种方法实现pid输出曲线按的模拟。(A two-dimensional fuzzy controll