{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T17:55:41Z","timestamp":1764784541098,"version":"build-2065373602"},"reference-count":26,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,11,10]],"date-time":"2020-11-10T00:00:00Z","timestamp":1604966400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001843","name":"Science and Engineering Research Board","doi-asserted-by":"publisher","award":["ECR\/2017\/000212"],"award-info":[{"award-number":["ECR\/2017\/000212"]}],"id":[{"id":"10.13039\/501100001843","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>In this investigation, self-learning salp swarm optimization (SLSSO) based proportional- integral-derivative (PID) controllers are proposed for a Doha reverse osmosis desalination plant. Since the Doha reverse osmosis plant (DROP) is interacting with a two-input-two-output (TITO) system, a decoupler is designed to nullify the interaction dynamics. Once the decoupler is designed properly, two PID controllers are tuned for two non-interacting loops by minimizing the integral-square-error (ISE). The ISEs for two loops are obtained in terms of alpha and beta parameters to simplify the simulation. Thus designed ISEs are minimized using SLSSO algorithm. In order to show the effectiveness of the proposed algorithm, the controller tuning is also accomplished using some state-of-the-art algorithms. Further, statistical analysis is presented to prove the effectiveness of SLSSO. In addition, the time domain specifications are presented for different test cases. The step responses are also shown for fixed and variable reference inputs for two loops. The quantitative and qualitative results presented show the effectiveness of SLSSO for the DROP system.<\/jats:p>","DOI":"10.3390\/a13110287","type":"journal-article","created":{"date-parts":[[2020,11,10]],"date-time":"2020-11-10T10:47:28Z","timestamp":1605005248000},"page":"287","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Self-Learning Salp Swarm Optimization Based PID Design of Doha RO Plant"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5403-4706","authenticated-orcid":false,"given":"Naresh","family":"Patnana","sequence":"first","affiliation":[{"name":"Electrical Engineering, National Institute of Technology, Raipur 492010, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Swapnajit","family":"Pattnaik","sequence":"additional","affiliation":[{"name":"Electrical Engineering, National Institute of Technology, Raipur 492010, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4047-7351","authenticated-orcid":false,"given":"Tarun","family":"Varshney","sequence":"additional","affiliation":[{"name":"Electrical and Electronics Engineering, ABES Engineering College, Ghaziabad 201009, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9279-1086","authenticated-orcid":false,"given":"Vinay Pratap","family":"Singh","sequence":"additional","affiliation":[{"name":"Electrical Engineering, Malaviya National Institute of Technology, Jaipur 302017, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"337","DOI":"10.2166\/aqua.2019.162","article-title":"A modified controller design based on symbiotic organisms search optimization for desalination system","volume":"68","author":"Rathore","year":"2019","journal-title":"J. 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