First Workshop on Enabling Predictive Science with Optimization and Uncertainty Quantification in HPC 2023 (EPSOUQ-HPC 2023)

被引：0

作者：

Georgiadou, Antigoni ^{[1
]}

Casey, Tiernan ^{[2
]}

机构：

[1] Oak Ridge National Laboratory, United States

[2] Sandia National Laboratories, United States

来源：

ACM International Conference Proceeding Series | 2023年

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D O I：

暂无

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摘要：

引用

共 10 条

[1] EPSOUQ-HPC 2024: Second Workshop on Enabling Predictive Science with Optimization and Uncertainty Quantification in HPC
Proceedings of SC 2024-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2024, : 370 - 371
[2] 2023 International Workshop on Performance, Portability, and Productivity in HPC (P3HPC)
Hill, Judith
Newburn, C.J.
Parker, Scott
Pennycook, John
ACM International Conference Proceeding Series, 2023, : 1005 - 1006
[3] Message from the HPC/DL 2023 Workshop Chairs
Proceedings - Symposium on Computer Architecture and High Performance Computing, 2023,
[4] First International Workshop on HPC Testing and Evaluation of Systems, Tools, and Software (HPCTESTS 2023)
Vergara, Verónica G. Melesse
Hadri, Bilel
Karakasis, Vasileios
ACM International Conference Proceeding Series, 2023, : 598 - 599
[5] Message from the Organizer of IXPUG Workshop HPC Asia 2023
Hanawa, Toshihiro
ACM International Conference Proceeding Series, 2023,
[6] Message from the Organizer of MMCP Workshop HPC Asia 2023
Pour, Neda Ebrahimi
Roller, Sabine
Takaki, Ryoji
ACM International Conference Proceeding Series, 2023,
[7] AI4DEV 2023: First Workshop on AI Assisted Software Development for HPC
Laguna, Ignacio
Georgakoudis, Giorgis
Parasyris, Konstantinos
ACM International Conference Proceeding Series, 2023,
[8] OpenCL-accelerated first-principles calculations of all-electron quantum perturbations on HPC resources (vol 11, 1156891, 2023)
Wu, Zhikun
Shang, Honghui
Wu, Yangjun
Zhang, Zhongcheng
Liu, Ying
Zhang, Yuyang
Ouyang, Yucheng
Cui, Huimin
Feng, Xiaobing
FRONTIERS IN CHEMISTRY, 2023, 11
[9] High-capacity device-independent quantum secure direct communication protocol using hyper-entanglement; AAPPS-DACG Workshop; Qi-Kun Xue receives the 2023 State Preeminent Science and Technology Award, China's top scientific honor; First Asian Physics Olympiad in Malaysia
AAPPS BULLETIN, 2024, 34 (01):
[10] This paper deals with model predictive control (MPC) for nonlinear systems using linear-parameter varying (LPV) embedding of the nonlinear dynamics (LPVMPC). The proposed LPVMPC can incorporate information of the future evolution of the scheduling parameter over the MPC prediction horizon with uncertainty bounds, which are used to construct anticipated scheduling tubes for robustification. Therefore, this approach is less conservative than the methods that only consider knowledge of the bounds on the scheduling parameter's rate of variation. The scheduling tubes are employed to synthesize online general polytopic invariant state tubes. The optimization problem of the proposed LPVMPC is a single quadratic program. Recursive feasibility is proven. A numerical example is presented for demonstrating the effectiveness of the proposed LPVMPC algorithm compared to nonlinear MPC and other standard approaches. © 2023 Elsevier Ltd. All rights reserved.
Abbas, Hossam Seddik
AUTOMATICA, 2024, 160

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