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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