Control Bootcamp: Linear Quadratic Gaussian (LQG)
Ғылым және технология
This lecture combines the optimal full-state feedback (e.g., LQR) with the optimal full-state estimator (e.g., LQE or Kalman Filter) to obtain the sensor-based linear quadratic Gaussian (LQG) controller.
These lectures follow Chapters 1 & 3 from:
Machine learning control, by Duriez, Brunton, & Noack
www.amazon.com/Machine-Learni...
Chapters available at: faculty.washington.edu/sbrunto...
This video was produced at the University of Washington
Пікірлер: 9
Podria decirme ,¿Cual seria el modelo en espacio de estados del sistema realimentado(lazo cerrado final) con SERVOCONTROL LQG(LQG + Accion Integral) ?porfavor estoy haciendo un proyecto con servocontrol LQG o algun libro en el que lo pueda encontrar
Could you tell me, what would be the state space model of the feedback system (final closed loop) with LQG SERVOCONTROL (LQG + Integral Action)? Please, I am doing a project with LQG servocontrol or some book where I can find it
Nice explanations, as are all other video's. Maybe good to refer to a very famous paper by J.C. Doyle called Guaranteed Margins for LQG regulators. Abstract - There are none.
@jeroendebest1711
3 жыл бұрын
Sorry, two videos later you exactly mention this particular paper. Cool!
There's a BKr in off diagonals, why does it called diagonal?
@simonb.979
2 жыл бұрын
i was actually wondering about that too. So, clearly it is coupled and the eigenvalues of the entire system have changed, right?
@parkerseth14
2 жыл бұрын
I think he meant to say triangular. The eigenvalues of a triangular matrix are exactly its diagonal entries, just like a diagonal matrix!
Anyone else confused by this magical backwards glass writing?
@peanutboy41
3 жыл бұрын
I was at too first but I think the video is mirrored