Skip to Main Content Skip to Search
Product Documentation

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 w of sys are assumed stochastic (process and/or measurement noise), and all outputs y are measured. The estimator est is returned in state-space form (SS object).

For a continuous-time plant sys with equations

estim uses the following equations to generate a plant output estimate and a state estimate , which are estimates of y(t)=C and x(t), respectively:

For a discrete-time plant sys with the following equations:

estim uses estimator equations similar to those for continuous-time to generate a plant output estimate and a state estimate , which are estimates of y[n] and x[n], respectively. These estimates are based on past measurements up to y[n-1].

est = estim(sys,L,sensors,known) handles more general plants sys with both known (deterministic) inputs u and stochastic inputs w, and both measured outputs y and nonmeasured outputs z.

The index vectors sensors and known specify which outputs of sys are measured (y), and which inputs of sys are known (u). The resulting estimator est, found using the following equations, uses both u and y to produce the output and state estimates.

Tips

You can use the functions place (pole placement) or kalman (Kalman filtering) to design an adequate estimator gain L. Note that the estimator poles (eigenvalues of A-LC) should be faster than the plant dynamics (eigenvalues of A) to ensure accurate estimation.

Examples

Consider a state-space model sys with seven outputs and four inputs. Suppose you designed a Kalman gain matrix L 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 | kalmd | lqgreg | place | predict | reg | ss | ssest

  


Free Control Systems Interactive Kit

Learn more about resources for designing, testing, and implementing control systems.

Get free kit

Trials Available

Try the latest control systems products.

Get trial software
 © 1984-2012- The MathWorks, Inc.    -   Site Help   -   Patents   -   Trademarks   -   Privacy Policy   -   Preventing Piracy   -   RSS