User`s guide

estim
11-71
estim handles both continuous- and discrete-time cases. You can use the
functions
place (pole placement) or kalman (Kalman filtering) to design an
adequate estimator gain . Note that the estimator poles (eigenvalues of
) should be faster than the plant dynamics (eigenvalues of ) to ensure
accurate estimation.
Example Consider a state-space model sys with seven outputs and four inputs. Suppose
you designed a Kalman gain matrix using outputs 4, 7, and 1 of the plant as
sensor measurements, and inputs 1,4, and 3 of the plant as known
(deterministic) inputs. You can then form the Kalma n estimator b y
sensors = [4,7,1];
known = [1,4,3];
est = estim(sys,L,sensors,known)
See the function kalman for direct Kalman e st imat or d e si gn.
See Also kalman Design Kalman estimator
place Pole placement
reg Form regulator given state-feedback and estimator
gains
x
ˆ
·
Ax
ˆ
B
2
uLyC
2
x
ˆ
D
22
u––()++=
y
ˆ
x
ˆ
C
2
I
x
ˆ
D
22
0
u+=
est
u (known)
y (sensors)
y
ˆ
x
ˆ
L
ALC
–
A
L