{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T10:37:22Z","timestamp":1760524642550,"version":"3.28.0"},"reference-count":31,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,6,25]],"date-time":"2024-06-25T00:00:00Z","timestamp":1719273600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,6,25]],"date-time":"2024-06-25T00:00:00Z","timestamp":1719273600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,6,25]]},"DOI":"10.23919\/ecc64448.2024.10591099","type":"proceedings-article","created":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T17:48:23Z","timestamp":1721843303000},"page":"1843-1850","source":"Crossref","is-referenced-by-count":2,"title":["Learning Iterative Solvers for Accurate and Fast Nonlinear Model Predictive Control via Unsupervised Training"],"prefix":"10.23919","author":[{"given":"Lukas","family":"L\u00fcken","sequence":"first","affiliation":[{"name":"TU Dortmund University,Chair of Process Automation Systems,Dortmund,Germany,44227"}]},{"given":"Sergio","family":"Lucia","sequence":"additional","affiliation":[{"name":"TU Dortmund University,Chair of Process Automation Systems,Dortmund,Germany,44227"}]}],"member":"263","reference":[{"volume-title":"Model Predictive Control: Theory, Computation, and Design","year":"2017","author":"Rawlings","key":"ref1"},{"volume-title":"Nonlinear Model Predictive Control, ser. Communications and Control Engineering","year":"2017","author":"Gr\u00fcne","key":"ref2"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2021.107291"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/PC52310.2021.9447448"},{"key":"ref5","article-title":"Neural networks for fast optimisation in model predictive control: A review","author":"Gonzalez","year":"2023","journal-title":"arXiv preprint"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/S0005-1098(01)00174-1"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.23919\/ACC.2018.8431275"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.2999556"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.23919\/ACC53348.2022.9867643"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ifacol.2023.10.545"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/0005-1098(95)00044-W"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.2969729"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/LCSYS.2018.2843682"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1002\/rnc.5696"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CDC42340.2020.9303895"},{"key":"ref16","article-title":"Approximate non-linear model predictive control with safety-augmented neural networks","author":"Hose","year":"2023","journal-title":"arXiv preprint"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2022.3216978"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.ifacol.2023.10.883"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/LCSYS.2020.2980479"},{"key":"ref20","first-page":"21 043","article-title":"Accelerating quadratic optimization with reinforcement learning","volume":"34","author":"Ichnowski","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"1","key":"ref21","first-page":"8562","article-title":"Learning to optimize: A primer and a benchmark","volume":"23","author":"Chen","year":"2022","journal-title":"The Journal of Machine Learning Research"},{"volume-title":"Numerical Optimization","year":"2006","author":"Nocedal","key":"ref22"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-004-0559-y"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1080\/02331939208843795"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2018.2872201"},{"key":"ref26","doi-asserted-by":"crossref","DOI":"10.1137\/1.9780898717761","volume-title":"Evaluating Derivatives, ser. Other Titles in Applied Mathematics","author":"Griewank","year":"2008"},{"key":"ref27","article-title":"Decoupled weight decay regularization","volume-title":"International Conference on Learning Representations","author":"Loshchilov","year":"2018"},{"key":"ref28","first-page":"12","article-title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","author":"Paszke","year":"2019","journal-title":"NeurIPS"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s12532-018-0139-4"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysconle.2007.06.013"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.conengprac.2023.105676"}],"event":{"name":"2024 European Control Conference (ECC)","start":{"date-parts":[[2024,6,25]]},"location":"Stockholm, Sweden","end":{"date-parts":[[2024,6,28]]}},"container-title":["2024 European Control Conference (ECC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10590709\/10590710\/10591099.pdf?arnumber=10591099","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T05:17:22Z","timestamp":1721884642000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10591099\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,25]]},"references-count":31,"URL":"https:\/\/doi.org\/10.23919\/ecc64448.2024.10591099","relation":{},"subject":[],"published":{"date-parts":[[2024,6,25]]}}}