| Function Reference | |
Form state estimator given estimator gain
Syntax
Description
est = estim(sys,L)
produces a state/output estimator est given the plant state-space model sys and the estimator gain L. All inputs 
of sys are assumed stochastic (process and/or measurement noise), and all outputs 
are measured. The estimator est is returned in state-space form (SS object). For a continuous-time plant sys with equations
estim generates plant output and state estimates 
and 
as given by the following model.
The discrete-time estimator has similar equations.
est = estim(sys,L,sensors,known)
handles more general plants sys with both known inputs 
and stochastic inputs 
, and both measured outputs 
and nonmeasured outputs 
.
The index vectors sensors and known specify which outputs 
are measured and which inputs 
are known. The resulting estimator est uses both 
and 
to produce the output and state estimates.
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 Kalman estimator by
See the function kalman for direct Kalman estimator design.
See Also
kalman
place
reg
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