Sylvester equation
The Sylvester equation, commonly encountered in control theory, is the matrix equation of the form
where
are
matrices.
are known. The problem is to find
.
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[edit] Existence and uniqueness of the solution
Using the Kronecker product notation and the vectorization operator
, we can rewrite the equation in the form
where
is the
identity matrix. In this form, the Sylvester equation can be seen as a linear system of dimension
.[1]
If
and
are the Jordan canonical forms of
and
, and
and
are their eigenvalues, one can write
Since
is upper triangular with diagonal elements
, the matrix on the left hand side is singular if and only if there exist
and
such that
.
Therefore, we have proved that the Sylvester equation has a unique solution if and only if
and
have no common eigenvalues.
[edit] Numerical solutions
A classical algorithm for the numerical solution of the Sylvester equation is the Bartels–Stewart algorithm, which consists of transforming
and
into Schur form by a QR algorithm, and then solving the resulting triangular system via back-substitution. This algorithm, whose computational cost is O
arithmetical operations, is used, among others, by LAPACK and the lyap function in GNU Octave.
[edit] See also
[edit] References
1. J. Sylvester, Sur l’equations en matrices
, C.R. Acad. Sci. Paris, 99 (1884), pp. 67 – 71, pp. 115 – 116.
2. R. H. Bartels and G. W. Stewart, Solution of the matrix equation
, Comm. ACM, 15 (1972), pp. 820 – 826.
3. R. Bhatia and P. Rosenthal, How and why to solve the operator equation
?, Bull. London Math. Soc., 29 (1997), pp. 1 – 21.
4. S.-G. Lee and Q.-P. Vu, Simultaneous solutions of Sylvester equations and idempotent matrices separating the joint spectrum, Linear Algebra and its Applications, 435 (2011), pp. 2097 – 2109.
[edit] Notes
- ^ However, rewriting the equation in this form is not advised for the numerical solution since this version is costly to solve and can be ill-conditioned.


