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lqe

Kalman estimator design for continuous-time systems.

Syntax

[L, P, E] = lqe(A, G, C, Q, R, N)
[L, P, E] = lqe(A, G, C, Q, R)

Input argument

A

State matrix: n x n matrix.

G

Defines a matrix linking the process noise to the states.

C

The output matrix, with dimensions (q x n), where q is the number of outputs.

Q

State-cost weighted matrix

R

Input-cost weighted matrix

N

Optional cross term matrix: 0 by default.

Output argument

L

Kalman gain matrix.

P

Solution of the Discrete Algebraic Riccati Equation.

E

Closed-loop pole locations

Description

The function computes the optimal steady-state feedback gain matrix, denoted as L, minimizing a quadratic cost function for a linear discrete state-space system model.

Example

c = 1;
m = 1;
k = 1;
A = [0, 2; -k/m, -c/m];
B = [0; 2/m];
G = [2 0 ; 0 2];
C = [2 0];
Q = [0.02 0; 0 0.02];
R = 0.02;
[l, p, e] = lqe(A, G, C, Q, R)

See also

lqr.

History

Version Description
1.0.0 initial version

Author

Allan CORNET

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