Abstract
Abstract There are several efficient direct solvers for structured systems of linear equations defining search directions in primal-dual interior point methods applied to constrained model predictive control problems. We propose reusing matrix decompositions of direct solvers as preconditioners in Krylov-subspace methods applied to subsequent iterations of the interior point method, which results in at least halving its asymptotic computational complexity. We also analyze sensitivity of direct solvers to the regularization parameters.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
