Learning for Online Mixed-Integer Model Predictive Control With Parametric Optimality Certificates-Reference-Cited by-同舟云学术

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Learning for Online Mixed-Integer Model Predictive Control With Parametric Optimality Certificates

Published:2023 Issue: Volume:7 Page:2215-2220
ISSN:2475-1456
Container-title:IEEE Control Systems Letters
language:
Short-container-title:IEEE Control Syst. Lett.

Author:

Russo Luigi¹^ORCID,Nair Siddharth H.²^ORCID,Glielmo Luigi³^ORCID,Borrelli Francesco²^ORCID

Affiliation:

1. Department of Engineering, Università del Sannio, Benevento, Italy

2. Model Predictive Control Lab, University of California at Berkeley, Berkeley, CA, USA

3. Department of Electrical Engineering and Information Technologies, Università di Napoli Federico II, Naples, Italy

Funder

Office of Naval Research

Ford Research Laboratories

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Control and Optimization,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7782633/9828546/10149475.pdf?arnumber=10149475

Reference22 articles.

1. CoCo: Online Mixed-Integer Control Via Supervised Learning

2. Online Mixed-Integer Optimization in Milliseconds

3. Near-Optimal Rapid MPC Using Neural Networks: A Primal-Dual Policy Learning Framework

4. Understanding deep learning (still) requires rethinking generalization

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Computationally efficient solution of mixed integer model predictive control problems via machine learning aided Benders Decomposition;Journal of Process Control;2024-05

2. Optimal energy management of grid-connected PV for HVAC cooling with ice thermal storage system;Journal of Energy Storage;2024-01

3. Equivariant Deep Learning of Mixed-Integer Optimal Control Solutions for Vehicle Decision Making and Motion Planning;IEEE Transactions on Control Systems Technology;2024

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