Parameter Identification Library
Updated 29 May 2023
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
Giampiero Campa (2023). Parameter Identification Library (https://github.com/giampy1969/simulink-parameter-identification-library/releases/tag/v1.2), GitHub. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
- Control Systems > System Identification Toolbox > Online Estimation >
- Simulink > Simulink Environment Fundamentals > Block Libraries >
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See release notes for this release on GitHub: https://github.com/giampy1969/simulink-parameter-identification-library/releases/tag/v1.2
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.
Changed info.xml file to avoid annoying messages within the last matlab versions.