文件列表:

NNCTRL20 (0, 2000-04-07)
NNCTRL20\Contents.m (4172, 2000-01-29)
NNCTRL20\CTRLDEMO (0, 1999-12-29)
NNCTRL20\CTRLDEMO\apcinit.m (2977, 2000-01-25)
NNCTRL20\CTRLDEMO\expdata.mat (16044, 1997-06-05)
NNCTRL20\CTRLDEMO\expinit.m (2542, 2000-01-24)
NNCTRL20\CTRLDEMO\fblinit.m (2631, 2000-01-26)
NNCTRL20\CTRLDEMO\fbltest.m (5635, 2000-01-26)
NNCTRL20\CTRLDEMO\ffinit.m (2687, 2000-01-25)
NNCTRL20\CTRLDEMO\forward.mat (632, 2000-01-25)
NNCTRL20\CTRLDEMO\forward2.mat (632, 2000-01-28)
NNCTRL20\CTRLDEMO\forward3.mat (912, 2000-01-26)
NNCTRL20\CTRLDEMO\imcinit.m (2675, 2000-01-25)
NNCTRL20\CTRLDEMO\initopt.mat (579, 1997-06-05)
NNCTRL20\CTRLDEMO\inverse.mat (632, 2000-01-25)
NNCTRL20\CTRLDEMO\inverse2.mat (580, 1997-06-05)
NNCTRL20\CTRLDEMO\inverse3.mat (579, 1997-06-05)
NNCTRL20\CTRLDEMO\invinit.m (2694, 2000-01-25)
NNCTRL20\CTRLDEMO\invinit1.m (2738, 2000-01-24)
NNCTRL20\CTRLDEMO\invinit2.m (3442, 2000-02-06)
NNCTRL20\CTRLDEMO\invtest.m (7956, 2000-01-24)
NNCTRL20\CTRLDEMO\lininit.m (3473, 2000-01-24)
NNCTRL20\CTRLDEMO\lintest.m (8782, 2000-01-22)
NNCTRL20\CTRLDEMO\lipdata.mat (16044, 1997-06-05)
NNCTRL20\CTRLDEMO\npcinit.m (3850, 2000-01-28)
NNCTRL20\CTRLDEMO\optctrl.mat (736, 2000-01-23)
NNCTRL20\CTRLDEMO\optinit.m (2716, 2000-01-24)
NNCTRL20\CTRLDEMO\optrinit.m (3535, 2000-01-23)
NNCTRL20\CTRLDEMO\opttest.m (6429, 2000-01-22)
NNCTRL20\CTRLDEMO\predtest.m (6403, 2000-01-28)
NNCTRL20\CTRLDEMO\smout.m (31, 1997-06-05)
NNCTRL20\CTRLDEMO\spm1.mdl (7967, 2000-01-24)
NNCTRL20\CTRLDEMO\spm2.mdl (8522, 2000-01-24)
NNCTRL20\CTRLDEMO\springm.m (89, 1997-06-05)
NNCTRL20\CTRLTOOL (0, 1999-12-29)
NNCTRL20\CTRLTOOL\apccon.m (10240, 2000-01-25)
NNCTRL20\CTRLTOOL\dio.m (784, 1997-06-05)
NNCTRL20\CTRLTOOL\diophant.m (903, 1997-09-18)
NNCTRL20\CTRLTOOL\experim.m (6526, 2000-01-25)
NNCTRL20\CTRLTOOL\fblcon.m (8900, 2000-01-26)
... ...

--OO-- Magnus Norgaard's NEURAL NETWORK BASED CONTROL SYSTEM DESIGN TOOLKIT (NNCTRL) Version 2 Department of Automation Building 326 2800 Lyngby, Denmark Technical University of Denmark --OO-- This collection of Matlab(r) files can be used for design and simulation of control systems based on multi-layer perceptron type neural networks. Tools are provided for: o Direct inverse control. o Control based on instantaneous linearization. o Optimal control. o Control by feedback linearization. o Nonlinear generalized predictive control. o Internal model control. o Feedforward control. A number of simple demonstration programs have been implemented to illustrate most of the concepts. Run these to get an idea about what the toolkit has to offer. Be careful with the demos, however. Due to problems with local minima the results can vary quite a lot between to runs of the same demo. In the current directory you should be able to find a brief manual in postscript format. Start by printing out this and study the release notes carefully. The release notes have also been witten in a file in this directory ("RELEASE"). The different functions do not contain "on-line" help regading their use. Instead you should study the text files 'Fblin', 'Feedforw', 'Imc', 'Instlin', 'Inverse', 'Npc', 'Optim' for an on-line explanation of the different concepts. The functions have not been thoroughly tested and thus you are likely to encounter bugs every once in a while. However, I hope I have managed to eliminate most of the bugs. Enjoy! - MN --OO-- Read the file "Contents.m" for a complete overview of the toolkit. DEMONSTRATION PROGRAMS: In order to run the demos you must go to the directory "CTRLDEMO" (and this directory must NOT be write protected!). !!Notice that you may have to resize the GUI window with the mouse if you are unable to read all the text because the font size is too large compared to the window size!! invtest : Demonstration of direct inverse control. fbltest : Demonstration of feedback linearization. lintest : Demonstration of instantaneous linearization based control. opttest : Demonstration of optimal control. predtest : Demonstration of predictive control. ffcon : A preliminary demonstration of PID + Feedforward control. imccon : A preliminary demonstration of internal model control.

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