Math 2.0

Linear and multilinear algebra; matrix theory Definition

Lyapunov equation

Builds on Square matrixHermitian matrixConjugate transposeSylvester equation

Definition

Let n≥1n \ge 1, let AA be an n×nn \times n complex matrix, and let QQ be an n×nn \times n Hermitian matrix. Write A∗A^* for the conjugate transpose of AA.

  1. The continuous Lyapunov equation is AX+XA∗+Q=0AX + XA^* + Q = 0 for an unknown n×nn \times n matrix XX.
  2. The discrete Lyapunov equation is AXA∗−X+Q=0AXA^* - X + Q = 0 for an unknown n×nn \times n matrix XX.

Remarks

The continuous equation is the Sylvester equation AX+XA∗=−QAX + XA^* = -Q. Many texts in control write it as A∗P+PA+Q=0A^* P + PA + Q = 0 instead, which is the same equation with A∗A^* in place of AA; for real AA this reads ATP+PA+Q=0A^T P + PA + Q = 0. If every eigenvalue of AA has negative real part, the continuous equation has the unique solution X=∫0∞eAtQeA∗t dtX = \int_0^\infty e^{At} Q e^{A^* t} \, dt, and XX is positive definite when QQ is. If every eigenvalue of AA has absolute value less than 11, the discrete equation has the unique solution X=∑k=0∞AkQ(A∗)kX = \sum_{k=0}^{\infty} A^k Q (A^*)^k. Example: for n=1n = 1, A=−1A = -1 and Q=2Q = 2, the continuous equation −2X+2=0-2X + 2 = 0 gives X=1X = 1. Without the eigenvalue condition a solution may fail to exist: for n=1n = 1, A=0A = 0 and Q=1Q = 1, the continuous equation reads 1=01 = 0.

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  1. Conjugate transpose concept
  2. Hermitian matrix concept
  3. Square matrix concept
  4. Sylvester equation concept
  5. Lyapunov equation definition

Further reading

  1. Web https://en.wikipedia.org/wiki/Lyapunov_equation
About this page
TagZFSZCMKJD1
URIm2://ZFSZCMKJD1
Kinddefinition
WritingW0 stub
MSC15A24, 93D05, 34D20
DefinesLyapunov equation
UsesSquare matrix, Hermitian matrix, Conjugate transpose, Sylvester equation
Changed2 November 2026

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