Convex invertible cones of state space systems

In the paper [CL1] the notion of a convex invertible cone,cic, of matrices was introduced and its geometry was studied. In that paper close connections were drawn between thiscic structure and the algebraic Lyapunov equation. In the present paper the same geometry is extended to triples of matrices andcics of minimal state space models are defined and explored. This structure is then used to study balancing, Hankel singular values, and simultaneous model order reduction for a set of systems. State spacecics are also examined in the context of the so-called matrix sign function algorithm commonly used to solve the algebraic Lyapunov and Riccati equations.

[1]  Nir Cohen,et al.  Convex invertible cones and the Lyapunov equation , 1997 .

[2]  Leiba Rodman,et al.  Algebraic Riccati equations , 1995 .

[3]  L. Balzer Accelerated convergence of the matrix sign function method of solving Lyapunov, Riccati and other matrix equations , 1980 .

[4]  G. Hewer,et al.  Necessary and sufficient conditions for balancing unstable systems , 1987 .

[5]  Charles R. Johnson,et al.  Convex Sets of Hermitian Matrices with Constant Inertia , 1985 .

[6]  Harald K. Wimmer,et al.  Inertia theorems for matrices, controllability, and linear vibrations , 1974 .

[7]  C. P. Therapos,et al.  Balancing transformations for unstable nonminimal linear systems , 1989 .

[8]  Charles R. Johnson,et al.  Topics in Matrix Analysis , 1991 .

[9]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[10]  Chi-Tsong Chen,et al.  A Generalization of the Inertia Theorem , 1973 .

[11]  K. Glover All optimal Hankel-norm approximations of linear multivariable systems and their L, ∞ -error bounds† , 1984 .

[12]  Carolyn L. Beck,et al.  Model reduction of multidimensional and uncertain systems , 1994, IEEE Trans. Autom. Control..

[13]  M. Safonov,et al.  A Schur method for balanced-truncation model reduction , 1989 .

[14]  George Phillip Barker,et al.  Common solutions to the Lyapunov equations , 1977 .

[15]  T. Söderström,et al.  On the asymptotic accuracy of pseudo-linear regression algorithms , 1984 .

[16]  E. Denman,et al.  The matrix sign function and computations in systems , 1976 .

[17]  David J. N. Limebeer,et al.  Linear Robust Control , 1994 .

[18]  U. Helmke Balanced realizations for linear systems: a variational approach , 1993 .

[19]  Fen Wu Induced L2 norm model reduction of polytopic uncertain linear systems , 1996, Autom..