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kalman

Design Kalman filter for state estimation.

Syntax

[kalmf, L, P, M, Z] = kalman(sys, Q, R, N)
[kalmf, L, P, M, Z] = kalman(sys, Q, R, N, sensors, known)

Input argument

sys

Plant model with process noise: state-space model.

Q

Process noise covariance: scalar or matrix.

R

Measurement noise covariance: scalar or matrix.

N

Noise cross covariance: scalar or matrix.

sensors

Measured outputs of sys: vector.

known

Known inputs of sys: vector.

Output argument

kalmf

Kalman estimator: state-space model

L

Filter gains: matrix

P

Steady-state error covariances: matrix

M

Innovation gains of state estimators: matrix

Z

Steady-state error covariances: matrix

Description

[kalmf, L, P] = kalman(sys, Q, R, N) generates a Kalman filter using the provided plant model sys and noise covariance matrices Q, R, and N.

The function calculates a Kalman filter suitable for application in a Kalman estimator, as depicted in the following diagram.

Example

A = [11.269   -0.4940    1.129; 1.0000         0         0;0    1.0000         0];
B = [-0.3832;  0.5919;  0.5191];
C = [1 0 0];
sys = ss(A,[B, B], C, 0);
Q = 1;
R = 1;
[kEst, l, p, m, z] = kalman(sys, Q, R, [])

See also

care, dare.

History

Version Description
1.0.0 initial version

Author

Allan CORNET

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