{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T00:31:50Z","timestamp":1773793910812,"version":"3.50.1"},"reference-count":38,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T00:00:00Z","timestamp":1752192000000},"content-version":"vor","delay-in-days":191,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Electrical and Computer Engineering"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:p>In the shipboard microgrids (SMGs), one of the most important issues is frequency stability. Any frequency fluctuation in this microgrid may lead to serious damage to a ship\u2019s essential equipment and even lead to power outages. Therefore, to improve the frequency stability in the SMG, various controllers have been used. In this paper, the model predictive control (MPC) controller is designed to enhance the frequency stability in the SMG. Also, reinforcement learning (RL) is used to improve the performance of the MPC controller, which because of changes of parameters and random disturbances may not be an accurate model, RL to continuously improve your policy. This combination makes the SMG capable of properly responding to the disturbances and uncertainties caused by the system parameters. To evaluate the performance of the proposed method (MPC\u2010RL) against disturbances and uncertainties on the SMG, several scenarios have been considered and compared with different controllers such as FDOFC and Fuzzy\u2010PI\u2010PSO, and the results. The proposed method is superior to other mentioned methods and significantly improves the frequency stability in SMG.<\/jats:p>","DOI":"10.1155\/jece\/3139447","type":"journal-article","created":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T10:04:29Z","timestamp":1752228269000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Improvement of Frequency Stability in Shipboard Microgrids Based on MPC\u2010Reinforcement Learning"],"prefix":"10.1155","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9335-7823","authenticated-orcid":false,"given":"Farhad","family":"Amiri","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6113-8930","authenticated-orcid":false,"given":"Sajad","family":"Sadr","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2025,7,11]]},"reference":[{"key":"e_1_2_10_1_2","article-title":"Designing a Multi-Objective Optimized Parallel Process Controller for Frequency Stabilization in an Islanded Microgrid","author":"Shayeghi H.","year":"2025","journal-title":"Journal of Operation and Automation in Power Engineering"},{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1002\/eng2.13095"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ref.2024.100625"},{"key":"e_1_2_10_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/tcsii.2021.3135962"},{"key":"e_1_2_10_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/tcsi.2021.3052774"},{"key":"e_1_2_10_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/access.2023.3312175"},{"key":"e_1_2_10_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/tie.2023.3303627"},{"key":"e_1_2_10_8_2","doi-asserted-by":"publisher","DOI":"10.3390\/jmse11122380"},{"key":"e_1_2_10_9_2","unstructured":"AmiriF.andHatamiA. 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