A sequential semidefinite programming method and an application in passive reduced-order modeling

Mathematics – Optimization and Control

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

We consider the solution of nonlinear programs with nonlinear semidefiniteness constraints. The need for an efficient exploitation of the cone of positive semidefinite matrices makes the solution of such nonlinear semidefinite programs more complicated than the solution of standard nonlinear programs. In particular, a suitable symmetrization procedure needs to be chosen for the linearization of the complementarity condition. The choice of the symmetrization procedure can be shifted in a very natural way to certain linear semidefinite subproblems, and can thus be reduced to a well-studied problem. The resulting sequential semidefinite programming (SSP) method is a generalization of the well-known SQP method for standard nonlinear programs. We present a sensitivity result for nonlinear semidefinite programs, and then based on this result, we give a self-contained proof of local quadratic convergence of the SSP method. We also describe a class of nonlinear semidefinite programs that arise in passive reduced-order modeling, and we report results of some numerical experiments with the SSP method applied to problems in that class.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A sequential semidefinite programming method and an application in passive reduced-order modeling does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A sequential semidefinite programming method and an application in passive reduced-order modeling, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A sequential semidefinite programming method and an application in passive reduced-order modeling will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-403547

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.