lqry

Form linear-quadratic (LQ) state-feedback regulator with output weighting.

📝 Syntax

• [K, S, e] = lqry(sys, Q, R, N)

📥 Input argument

• sys - LTI model

• Q - State-cost weighted matrix

• R - Input-cost weighted matrix

• N - Optional cross term matrix: 0 by default.

📤 Output argument

• K - Optimal gain: row vector.

• S - Solution of the Algebraic Riccati Equation.

• e - Poles of the closed-loop system: column vector.

📄 Description

The function lqry computes and returns the optimal gain matrix (K), the Riccati solution (S), and the closed-loop eigenvalues (e) for a given state-space model (sys) with specified weights (Q, R, N).

The plant data is defined by the matrices A, B, C, and D, representing continuous- or discrete-time dynamics.

If the parameter N is not provided, it defaults to N=0.

The closed-loop eigenvalues are determined by the eigenvalues of the matrix A - B * K.

💡 Example

A = [0.6, 0.25; 0, 0.9];
B = [0; 10];
C = [11, 0];
D = 0;
Q = 2;
R = 1;
[K, S, e] = lqry(A, B, C, D, Q, R)

🔗 See also

lqr.

🕔 History

Version	📄 Description
1.0.0	initial version