登录
首页 » matlab » Advanced-PID-control

Advanced-PID-control

于 2012-06-23 发布 文件大小:208KB
0 201
下载积分: 1 下载次数: 7

代码说明:

  先进PID控制matlab仿真光盘的全套源程序,欢迎大家下载,谢谢(Advanced PID control matlab simulation CD-ROM full source code, are welcome to download, thank you.)

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • Gui-design
    收集在一起的学习matlab Gui设计的学习资料,讲解很详细清楚(Gather together to learn matlab Gui design learning materials, to explain very detailed and clear)
    2012-08-13 15:10:58下载
    积分:1
  • snkae-model
    基于matlabGUI 的图形化界面,展示了snake能量边缘算法检测,并通过调节参数查看算法效果(MatlabGUI-based graphical interface that shows the snake energy edge detection algorithm, and the algorithm by adjusting the parameters to see the effect of)
    2013-12-09 14:26:55下载
    积分:1
  • dualconverter
    basic dual converter operaiton
    2010-10-02 13:26:08下载
    积分:1
  • dfsorigin
    DFS in Matlab, Depth First Search
    2009-12-10 00:49:58下载
    积分:1
  • MD1
    MD1system design using Matlab GUI
    2015-03-10 15:49:48下载
    积分:1
  • sbmlr
    本代码为特征提取代码,是从高维数据到低维数据(The source code for the feature selection to reduce the high-dimensional data low-dimensional data)
    2015-03-26 20:22:11下载
    积分:1
  • idfig02
    idfig function for wavelet analysis
    2013-05-15 03:32:59下载
    积分:1
  • ovsf
    orthogonal variable spreading factor (OVSF) is an implementation of Code division multiple access (CDMA) where before each signal is transmitted, the spectrum is spread through the use of a user s code. User s codes are carefully chosen to be mutually orthogonal to each other. These codes are derived from an OVSF code tree, and each user is given a different, unique code. An OVSF code tree is a complete binary tree that reflects the construction of Hadamard matrices.
    2010-05-24 01:30:22下载
    积分:1
  • 二次规划问题和MATLAB函数quadprog的使用小结
    说明:  二次规划问题和MATLAB函数quadprog的使用小结(Summary of quadratic programming problem and the use of Matlab function quadprog)
    2020-05-13 22:11:01下载
    积分:1
  • kmedian
    The method works as follows. 1. For a data set with dimensionality, d, compute the variance of data in each dimension (column). 2. Find the column with maximum variance call it cvmax and sort it in any order. 3. Divide the data points of cvmax into K subsets, where K is the desired number of clusters. 4. Find the median of each subset. 5. Use the corresponding data points (vectors) for each median to initialize the cluster centers.
    2013-08-10 03:45:31下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载