Solving
interpolation problems via generalized eigenvalue minimization
Solving
interpolation problems via generalized eigenvalue minimization
V. Balakrishnan, E. Feron, S. Boyd and L. El Ghaoui
Proc. American Control Conf., pages 2921-2922, Chicago, Illinois, June 1992
Abstract:
A number of problems in the analysis and design of control systems
may be reformulated as the problem of minimizing the largest generalized
eigenvalue of a pair of symmetric matrices which depend affinely on
the decision variables, subject to constraints that are
linear matrix inequalities. For these generalized eigenvalue
problems, there exist numerical algorithms that are guaranteed to be
globally convergent, have polynomial worst-case complexity, and
stopping criteria that guarantee desired accuracy. In this paper,
we show how a number of important interpolation problems in control
may be solved via generalized eigenvalue minimization.
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