GPU-Accelerated PD-IPM for Real-Time Model Predictive Control in Integrated Missile Guidance and Control Systems.

Sanghyeon Lee, Heoncheol Lee, Yunyoung Kim, Jaehyun Kim, Wonseok Choi

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Improving reconstructions in nanotomography for homogeneous materialsNanoscale advances · 2024
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sanghyeon LeeResearch Institute of Manufacturing and Productivity, Kumoh National Institute of Technology, Gumi 39177, Gyeongbuk, Korea.ORCID 0000-0001-6077-839X

Heoncheol LeeDepartment of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Gyeongbuk, Korea.ORCID 0000-0003-2962-3474

Yunyoung KimPrecision Guided Munition R&D Laboratory, LIGNEX1, Seongnam 13488, Gyeonggi, Korea.

Jaehyun KimPrecision Guided Munition R&D Laboratory, LIGNEX1, Seongnam 13488, Gyeonggi, Korea.

Wonseok ChoiPrecision Guided Munition R&D Laboratory, LIGNEX1, Seongnam 13488, Gyeonggi, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper addresses the problem of real-time model predictive control (MPC) in the integrated guidance and control (IGC) of missile systems. When the primal-dual interior point method (PD-IPM), which is a convex optimization method, is used as an optimization solution for the MPC, the real-time performance of PD-IPM degenerates due to the elevated computation time in checking the Karush-Kuhn-Tucker (KKT) conditions in PD-IPM. This paper proposes a graphics processing unit (GPU)-based method to parallelize and accelerate PD-IPM for real-time MPC. The real-time performance of the proposed method was tested and analyzed on a widely-used embedded system. The comparison results with the conventional PD-IPM and other methods showed that the proposed method improved the real-time performance by reducing the computation time significantly.

Indexed as

Algorithmsgraphics processing unitintegrated missile guidance and controlmodel predictive controlprimal-dual interior point methodreal-time systems

Identifiers

PMID35746292

DOI10.3390/s22124512

PMCPMC9231268

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.