Control System Toolbox™

estim - Form state estimator given estimator gain

Syntax

est = estim(sys,L)
est = estim(sys,L,sensors,known)

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

sensors = [4,7,1];
known = [1,4,3];
est = estim(sys,L,sensors,known)

See the function kalman for direct Kalman estimator design.

See Also

kalman, place, reg

esort

evalfr