Approximation theory for linear-quadratic-Guassian optimal control of flexible structures
SIAM Journal on Control and Optimization
SIAM Journal on Control and Optimization
An introduction to infinite-dimensional linear systems theory
An introduction to infinite-dimensional linear systems theory
Mesh Independence of Kleinman-Newton Iterations for Riccati Equations in Hilbert Space
SIAM Journal on Control and Optimization
International Journal of Computer Mathematics - RECENT ADVANCES IN COMPUTATIONAL AND APPLIED MATHEMATICS IN SCIENCE AND ENGINEERING
Inexact Kleinman-Newton Method for Riccati Equations
SIAM Journal on Matrix Analysis and Applications
A comparison of balanced truncation methods for closed loop systems
ACC'09 Proceedings of the 2009 conference on American Control Conference
Approximation of low rank solutions for linear quadratic control of partial differential equations
Computational Optimization and Applications
Balanced POD for model reduction of linear PDE systems: convergence theory
Numerische Mathematik
Proper orthogonal decomposition for reduced basis feedback controllers for parabolic equations
Mathematical and Computer Modelling: An International Journal
Numerical methods for approximating functional gains in LQR boundary control problems
Mathematical and Computer Modelling: An International Journal
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A mathematical model of a physical system is never perfect; therefore, robust control laws are necessary for guaranteed stabilization of the nominal model and also "nearby" systems, including hopefully the actual physical system. We consider the computation of a robust control law for large-scale finite dimensional linear systems and a class of linear distributed parameter systems. The controller is robust with respect to left coprime factor perturbations of the nominal system. We present an algorithm based on balanced proper orthogonal decomposition to compute the nonstandard features of this robust control law. Convergence theory is given, and numerical results are presented for two partial differential equation systems.