A study of matrix equations

Matrix equations have been studied by Mathematicians for many years. Interest in them has grown due to the fact that these equations arise in many different fields such as vibration analysis, optimal control, stability theory etc. This thesis is concerned with methods of solution of various matrix equations with particular emphasis on quadratic matrix equations. Large scale numerical techniques are not investigated but algebraic aspects of matrix equations are considered. Many established methods are described and the solution of a matrix equation by consideration of an equivalent system of multivariable polynomial equations is investigated. Matrix equations are also solved by a method which combines the given equation with the characteristic equation of the unknown matrix. Several iterative processes used for the solution of scalar equations are applied directly to the matrix equation. A new iterative process based on elimination methods is also described and examples given. The solutions of the equation x2 = P are obtained by a method which derives a set of polynomial equations connecting the characteristic coefficients of X and P. It is also shown that the equation X2 = P has an infinite number of solutions if P is a derogatory matrix. Acknowledgement

From Algebraic Riccati equations to unilateral quadratic matrix equations: old and new algorithms

The problem of reducing an algebraic Riccati equation $XCX-AX-XD+B=0$ to a unilateral quadratic matrix equation (UQME) of the kind $PX^2+QX+R$ is analyzed. New reductions are introduced which enable one to prove some theoretical and computational properties. In particular we show that the structure preserving doubling algorithm of B.D.O. Anderson [Internat. J. Control, 1978] is nothing else but the cyclic reduction algorithm applied to a suitable UQME. A new algorithm obtained by complementing our reductions with the shrink-and-shift tech- nique of Ramaswami is presented. Finally, faster algorithms which require some non-singularity conditions, are designed. The non-singularity re- striction is relaxed by introducing a suitable similarity transformation of the Hamiltonian

Iterative and doubling algorithms for Riccati-type matrix equations: a comparative introduction

We review a family of algorithms for Lyapunov- and Riccati-type equations which are all related to each other by the idea of \emph{doubling}: they construct the iterate $Q_k = X_{2^k}$ of another naturally-arising fixed-point iteration $(X_h)$ via a sort of repeated squaring. The equations we consider are Stein equations $X - A^*XA=Q$, Lyapunov equations $A^*X+XA+Q=0$, discrete-time algebraic Riccati equations $X=Q+A^*X(I+GX)^{-1}A$, continuous-time algebraic Riccati equations $Q+A^*X+XA-XGX=0$, palindromic quadratic matrix equations $A+QY+A^*Y^2=0$, and nonlinear matrix equations $X+A^*X^{-1}A=Q$. We draw comparisons among these algorithms, highlight the connections between them and to other algorithms such as subspace iteration, and discuss open issues in their theory.Comment: Review article for GAMM Mitteilunge

Nonsymmetric algebraic Riccati equations associated with an M-matrix: recent advances and algorithms

We survey on theoretical properties and algorithms concerning the problem of solving a nonsymmetric algebraic Riccati equation, and we report on some known methods and new algorithmic advances. In particular, some results on the number of positive solutions are proved and a careful convergence analysis of Newton\u27s iteration is carried out in the cases of interest where some singularity conditions are encountered. From this analysis we determine initial approximations which still guarantee the quadratic convergence