Transfer Function of an Observer designed by Kalman filter

May 16, 2008 3 Replies

Hi to all,



Another question of mine is about the transfer function of an observer designed using a Kalman filter. How can we convert the observer equation to a good form to analyze the frequency response of the oberserver?



The observer equation is:



xdot=Ax+Bu+L(y-Cx);



where L is the Kalman gain, y is the measurement and the input u=0.



I want to get the transfer function between some states inside x and y. I have acceleration estimates inside x, and y measurements are speed measurements. If I take the input as y, and choose the acceleration states from x, I am supposed to get a differentiator characteristic.



I have 9 states which means my Kalman gain is a vector with 9 elements. My Kalman gain is updated in everytime step and converges to constant values for all of the states.



Regards



Volkan


Hi to all,

Another question of mine is about the transfer function of an observer designed using a Kalman filter. How can we convert the observer equation to a good form to analyze the frequency response of the oberserver?

The observer equation is:

xdot=Ax+Bu+L(y-Cx);

where L is the Kalman gain, y is the measurement and the input u=0.

I want to get the transfer function between some states inside x and y. I have acceleration estimates inside x, and y measurements are speed measurements. If I take the input as y, and choose the acceleration states from x, I am supposed to get a differentiator characteristic.

I have 9 states which means my Kalman gain is a vector with 9 elements. My Kalman gain is updated in everytime step and converges to constant values for all of the states.

Regards

Volkan

Once your Kalman gain has settled out, your system is a linear time invariant system. If u is zero then you can eliminate it from the equation. Rearranging you system, you get:

xdot = (A - LC)x + Ly

If you let Cn be a selector output gain that chooses the nth element out of x (i.e. if you want x1 then C1 = [1 0 0 0 0...], if you want x4 then C4 = [0 0 0 1 0 ...]). Then your transfer function from y to xn is just

Hn = Cn * (Is - (A - LC))^-1 * L

Assuming you're in s -- 'Is' in this case is the identity matrix times s.

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