Title :
Computation of approximate null vectors of Sylvester and Lyapunov operators
Author :
Ghavimi, Ali R. ; Laub, Alan J.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA
fDate :
2/1/1995 12:00:00 AM
Abstract :
This paper describes an effective algorithm for computing approximate null vectors of certain matrix operators associated with Sylvester or Lyapunov equations. The singular value decomposition and rank-revealing QR methods are two widely used stable algorithms for numerical determination of the rank and nullity of a matrix A. These methods, however, are not readily applicable to Sylvester and Lyapunov operators since they require on the order of n6 arithmetic operations on order n2 data. For these problems, a variant of inverse power iteration is employed to compute orthonormal bases for singular subspaces associated with the small singular values. The method is practical since it relies only on the ability to solve a Sylvester or Lyapunov equation. Certain practical aspects are considered, and a direct refinement technique is proposed to enhance the convergence of the algorithm
Keywords :
Lyapunov matrix equations; convergence of numerical methods; iterative methods; linear systems; singular value decomposition; vectors; Lyapunov operators; Sylvester operators; approximate null vectors; convergence; inverse power iteration; iteration algorithm; matrix operators; singular subspaces; singular value decomposition; Adaptive control; Automatic control; Control systems; Equations; Matrix decomposition; Nonlinear dynamical systems; Nonlinear systems; Programmable control; Robust stability; Vehicles;
Journal_Title :
Automatic Control, IEEE Transactions on