So what? Why bother? The professor didn't make that clear! I doubt he has ever used an observer in an actual application. The purpose of observers is to estimate states which are usually higher derivatives of the measured state. For instance in motion control it is common to get position feedback. Calculating the velocity and acceleration accurately is impossible if the feed back does not have extremely fine resolution and there is no sample jitter. Knowing the actual velocity or estimating the actual velocity and acceleration is often key to good close loop control. The observer allows one to estimate the velocity, acceleration and sometimes even jerk or 3rd derivative of position. This allows for much better control because now higher derivative gains can be used in the closed loop control. However, all of this is USELESS unless you first have a good model of plant so you know what the A and B matrices are within a few percent. This requires system identification. You must learn how to find the values for the A and B matrices before observer control will work.
i love the way you explain it, so understable
simple and easily understandable, thanks a lot
I love how he keeps explaining all the theory in depth and at the end he goes like does this work? no!
Excelent lecture. I was wondering if you were planning to talk about Kalman Filters?
Thank you. I love this lecture. Thanks again.
Wow how he can explain this topic in a easy way thank you for sharing
Best ever lecture
Please...how can obtain the observer gain by the linear matrix inequality method
Nice Explanation! Any plan to expand this to cover Kalman Filters?
Thank you
Love this video :) Thanks
So what? Why bother? The professor didn't make that clear! I doubt he has ever used an observer in an actual application.
The purpose of observers is to estimate states which are usually higher derivatives of the measured state. For instance in motion control it is common to get position feedback. Calculating the velocity and acceleration accurately is impossible if the feed back does not have extremely fine resolution and there is no sample jitter.
Knowing the actual velocity or estimating the actual velocity and acceleration is often key to good close loop control. The observer allows one to estimate the velocity, acceleration and sometimes even jerk or 3rd derivative of position.
This allows for much better control because now higher derivative gains can be used in the closed loop control.
However, all of this is USELESS unless you first have a good model of plant so you know what the A and B matrices are within a few percent.
This requires system identification. You must learn how to find the values for the A and B matrices before observer control will work.