Design and simulation optimal controllers for SEPIC converter. Used Model Kalman filtering, also known as linear quadratic estimation (LQE) for recovering the states. Compare two controllers: A linear-quadratic regulator (LQR) and a predictive control (MPC) . The calculations made on Matlab, and simulated on Simulink
-
Notifications
You must be signed in to change notification settings - Fork 7
Designed and simulated the optimal controllers for SEPIC converter. Used Model Kalman filtering, also known as Linear Quadratic Estimation (LQE) for recovering the states. Compare two controllers: A Linear-Quadratic Regulator (LQR) and a Model Predictive Control (MPC) . The calculations made on Matlab, and simulated on Simulink.
bermeom/optimal-control-SEPIC-converter
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
Designed and simulated the optimal controllers for SEPIC converter. Used Model Kalman filtering, also known as Linear Quadratic Estimation (LQE) for recovering the states. Compare two controllers: A Linear-Quadratic Regulator (LQR) and a Model Predictive Control (MPC) . The calculations made on Matlab, and simulated on Simulink.
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published