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PIL

version 1.1.0.0 (211 KB) by Giampiero Campa
Parameter Identification Library

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Updated 20 Dec 2008

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This Simulink library is a collection of
blocks that perform Parameter Identification
through the most rewarded frequency and time
domain linear regression methods. It works
in Matlab 5.3.1 as well as in later versions.

Main examples are:

-) Recursive Least Squares (RLS).
-) Simple Windowed Regression (LLS).
-) Local Weighted Regression (LWR).
-) Fourier Transform Regression (FTR).

Two example on Linear and Nonlinear Aircraft
Parameter Identification are included in the library.

IMPORTANT, all of these blocks REQUIRE SMXL
(the Simulink Matrix Library) freely available in the File exchange section of the MATLAB Central website.

Giampy, October 2001

Comments and Ratings (11)

yang li

Hellol,
I wish the author can complement the files:
Main examples are:

-) Recursive Least Squares (RLS).
-) Simple Windowed Regression (LLS).
-) Local Weighted Regression (LWR).
-) Fourier Transform Regression (FTR).


Two example on Linear and Nonlinear Aircraft
Parameter Identification are included in the library.

Best Wishes

kim l

PIL is a more the famous (or less than shoul)python image library :)

Julian Stoev

I was just going to program it myself and found a reference in sci.eng.control. Have to check how it works, but this should be really good!

Sebi Sisca

Thanks a lot, you are a life saver

Gelar Budiman

ZAFAR ALI

BEST

shahin mokhtare

Iman abdelhamid

Abas Mohamed

Mazen Nehma

Updates

1.1.0.0

Streamlined the nonlinear identification example, and inserted additional explanations to both examples. I've also changed one logical operation that prevented the Simulink implementation of the LWR-RD block to work with later versions of matlab.

1.0.0.0

Changed info.xml file to avoid annoying messages within the last matlab versions.

Removed extra dir info from zip file

Renamed everything lowercase

Changed name, should have done that long ago.

Updated signature and info.xml file.

MATLAB Release Compatibility
Created with R11.1
Compatible with any release
Platform Compatibility
Windows macOS Linux