Iterative Learning with State-Dependent Riccati Equation
Version 1.0.2 (150 KB) von
Saeed Rafee Nekoo
These files present learning and error reduction with the SDRE controller augmented by an iterative learning control approach.
The codes are named by the order of the sections of the following report:
S. R. Nekoo, J. Á. Acosta, G. Heredia and A. Ollero, "A PD-type state-dependent Riccati equation with iterative learning augmentation for mechanical systems," in IEEE/CAA Journal of Automatica Sinica, doi: 10.1109/JAS.2022.105533.
In the codes, a transformation of the conventional SDRE to a PD-type has been presented which could be seen in Section 3.
The codes of Section 5 are for simulations and the codes of Section 6 are for experiments. To run the experiment codes, having a setup with Arduino digital board is necessary, equipped with optical encoder feedback. To run the experiment code, load the “.mat” data file first and plot the results.
The details, formulations, and more information could be found in the above reference. A video of the experiments could be seen on the journal website in the media section.
Please download the data “.mat” file for the last code from the journal’s website.
Zitieren als
S. R. Nekoo, J. Á. Acosta, G. Heredia and A. Ollero, "A PD-type state-dependent Riccati equation with iterative learning augmentation for mechanical systems," in IEEE/CAA Journal of Automatica Sinica, doi: 10.1109/JAS.2022.105533.
Kompatibilität der MATLAB-Version
Erstellt mit
R2022a
Kompatibel mit allen Versionen
Plattform-Kompatibilität
Windows macOS LinuxTags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Live Editor erkunden
Erstellen Sie Skripte mit Code, Ausgabe und formatiertem Text in einem einzigen ausführbaren Dokument.
Version | Veröffentlicht | Versionshinweise | |
---|---|---|---|
1.0.2 | Text update. |
||
1.0.1 | Update. |
||
1.0.0 |