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
Last updated
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