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Complexity Certific...
Complexity Certification of Proximal-Point Methods for Numerically Stable Quadratic Programming
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- Arnström, Daniel (author)
- Linköpings universitet,Reglerteknik,Tekniska fakulteten
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- Bemporad, Alberto (author)
- IMT Sch Adv Studies Lucca, Italy
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- Axehill, Daniel (author)
- Linköpings universitet,Reglerteknik,Tekniska fakulteten
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(creator_code:org_t)
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2021
- 2021
- English.
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In: IEEE Control Systems Letters. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2475-1456. ; 5:4, s. 1381-1386
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Abstract
Subject headings
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- When solving a quadratic program (QP), one can improve the numerical stability of any QP solver by performing proximal-point outer iterations, resulting in solving a sequence of better conditioned QPs. In this letter we present a method which, for a given multi-parametric quadratic program (mpQP) and any polyhedral set of parameters, determines which sequences of QPs will have to be solved when using outer proximal-point iterations. By knowing this sequence, bounds on the worst-case complexity of the method can be obtained, which is of importance in, for example, real-time model predictive control (MPC) applications. Moreover, we combine the proposed method with previous work on complexity certification for active-set methods to obtain a more detailed certification of the proximal-point methods complexity, namely the total number of inner iterations.
Subject headings
- NATURVETENSKAP -- Matematik -- Beräkningsmatematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Computational Mathematics (hsv//eng)
Keyword
- Optimization algorithms; predictive control for linear systems
Publication and Content Type
- ref (subject category)
- art (subject category)
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