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Direct Parallel Computations of Second-Order Search Directions for Model Predictive Control
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-6957-2603
2019 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 64, no 7, p. 2845-2860Article in journal (Refereed) Published
Abstract [en]

Model predictive control (MPC) is one of the most widely spread advanced control schemes in industry today. In MPC, a constrained finite-time optimal control (CFTOC) problem is solved at each iteration in the control loop. The CFTOC problem can be solved using, for example, second-order methods, such as interior-point or active-set methods, where the computationally most demanding part often consists of computing the sequence of second-order search directions. Each search direction can be computed by solving a set of linear equations that corresponds to solving an unconstrained finite-time optimal control (UFTOC) problem. In this paper, different direct (noniterative) parallel algorithms for solving UFTOC problems are presented. The parallel algorithms are all based on a recursive variable elimination and solution propagation technique. Numerical evaluations of one of the parallel algorithms indicate that a significant boost in performance can be obtained, which can facilitate high-performance second-order MPC solvers.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2019. Vol. 64, no 7, p. 2845-2860
Keywords [en]
MPC; optimization; parallel; Riccati recursion
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-158940DOI: 10.1109/TAC.2018.2880405ISI: 000473489700014OAI: oai:DiVA.org:liu-158940DiVA, id: diva2:1338188
Note

Funding Agencies|Swedish Research Council (VR); Center for Industrial Information Technology (CENIIT); Excellence Center at Linkoping-Lund on Information Technology (ELLIIT)

Available from: 2019-07-20 Created: 2019-07-20 Last updated: 2019-10-29

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