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lqrd
[Kd,S,e] = lqrd(A,B,Q,R,Ts)
[Kd,S,e] = lqrd(A,B,Q,R,N,Ts)
lqrd designs a discrete full-state-feedback regulator that has response characteristics similar to a continuous state-feedback regulator designed using lqr. This command is useful to design a gain matrix for digital implementation after a satisfactory continuous state-feedback gain has been designed.
[Kd,S,e] = lqrd(A,B,Q,R,Ts) calculates the discrete state-feedback law
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that minimizes a discrete cost function equivalent to the continuous cost function
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The matrices A and B specify the continuous plant dynamics
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and Ts specifies the sample time of the discrete regulator. Also returned are the solution S of the discrete Riccati equation for the discretized problem and the discrete closed-loop eigenvalues e = eig(Ad-Bd*Kd).
[Kd,S,e] = lqrd(A,B,Q,R,N,Ts) solves the more general problem with a cross-coupling term in the cost function.
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The equivalent discrete gain matrix Kd is determined by discretizing the continuous plant and weighting matrices using the sample time Ts and the zero-order hold approximation.
With the notation

the discretized plant has equations
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and the weighting matrices for the equivalent discrete cost function are

The integrals are computed using matrix exponential formulas due to Van Loan (see [2]). The plant is discretized using c2d and the gain matrix is computed from the discretized data using dlqr.
The discretized problem data should meet the requirements for dlqr.
[1] Franklin, G.F., J.D. Powell, and M.L. Workman, Digital Control of Dynamic Systems, Second Edition, Addison-Wesley, 1980, pp. 439-440.
[2] Van Loan, C.F., "Computing Integrals Involving the Matrix Exponential," IEEE Trans. Automatic Control, AC-23, June 1978.
![]() | lqr | lqry | ![]() |

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