Monte-Carlo Simulations & Robustness Analysis
These are the files for Chapter 7 for the book " Practical Design and Application of Model Predictive Control" by Elsevier (eBook ISBN: 9780128139196, Paperback ISBN: 9780128139189).
These files pertain to multiple MPC controllers for the ship navigation. In particular, we are controlling the forward speed and turning rate. In this submission Monte-Carlo simulations are run to test the designed MPC controllers. Follow the below steps to run and analyze the simulations.
Run Chapter_7_Section_2.m script that can be found in Chapter_7/Section_2. This will load and plot randomly generated current, wind and wave data.
Open Chapter_6_Multiple_MPC_Final.slx that can be found in Chapter_7/Section_4 to explore the structure of the controller+ship model.
Run Chapter_7_Section_4.m script that can be found in Chapter_7/Section_4. This will load the 12 MPC controllers’ data, current, wind and wave data, and run 150 Monte-Carlo simulations. It will also calculate tracking performance of the controller for both forward speed of the ship and the turning rate.
Run Chapter_7_Section_5.m script that can be found in Chapter_7/Section_5. This will load update the weights of the the 12 MPC controllers that were used in Chapter_7/Section_4 . It will also run 150 Monte-Carlo simulations, calculate tracking performance of the controller for both forward speed of the ship and the turning rate.
Similar to the two sections above, run Chapter_7_Section_6.m which has 3 different MPC tuning weights. Three 150 Monte-Carlo simulations are run by the script. Results are shown with legends for the 3 different weights. This allows the user to draw conclusion between weights of MPC controller and tracking performance.
Zitieren als
Nassim Khaled (2024). Monte-Carlo Simulations & Robustness Analysis (https://www.mathworks.com/matlabcentral/fileexchange/67871-monte-carlo-simulations-robustness-analysis), MATLAB Central File Exchange. Abgerufen.
Kompatibilität der MATLAB-Version
Plattform-Kompatibilität
Windows macOS LinuxKategorien
Tags
Quellenangaben
Inspiriert: Synthetic Data Generation by Sequential Monte Carlo
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.
Chapter_7/Section_2
Chapter_7/Section_4
Chapter_7/Section_5
Chapter_7/Section_6
Chapter_7/Section_4
Chapter_7/Section_5
Chapter_7/Section_6
Version | Veröffentlicht | Versionshinweise | |
---|---|---|---|
1.0.0.1 | Added website. |
|
|
1.0.0.0 |
|