{"id":"https://openalex.org/W7135172066","doi":"https://doi.org/10.1109/tetci.2026.3669780","title":"A Deep Learning Approach for Gain-Scheduled PID Control Design via Advanced Supervisory Controllers","display_name":"A Deep Learning Approach for Gain-Scheduled PID Control Design via Advanced Supervisory Controllers","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7135172066","doi":"https://doi.org/10.1109/tetci.2026.3669780"},"language":null,"primary_location":{"id":"doi:10.1109/tetci.2026.3669780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2026.3669780","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046014934","display_name":"Ercan Atam","orcid":"https://orcid.org/0000-0002-6073-5143"},"institutions":[{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ercan Atam","raw_affiliation_strings":["Institute for Data Science &amp; Artificial Intelligence of Bo&#x011F;azi&#x00E7;i University, &#x0130;stanbul, T&#x00FC;rkiye"],"raw_orcid":"https://orcid.org/0000-0002-6073-5143","affiliations":[{"raw_affiliation_string":"Institute for Data Science &amp; Artificial Intelligence of Bo&#x011F;azi&#x00E7;i University, &#x0130;stanbul, T&#x00FC;rkiye","institution_ids":["https://openalex.org/I2799978770"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037542463","display_name":"Atakan Zeybek","orcid":null},"institutions":[{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Atakan Zeybek","raw_affiliation_strings":["Institute for Data Science &amp; Artificial Intelligence of Bo&#x011F;azi&#x00E7;i University, &#x0130;stanbul, T&#x00FC;rkiye"],"raw_orcid":"https://orcid.org/0009-0006-9711-0362","affiliations":[{"raw_affiliation_string":"Institute for Data Science &amp; Artificial Intelligence of Bo&#x011F;azi&#x00E7;i University, &#x0130;stanbul, T&#x00FC;rkiye","institution_ids":["https://openalex.org/I2799978770"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128943150","display_name":"\u015eaziye Bet\u00fcl \u00d6zate\u015f","orcid":null},"institutions":[{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"\u015eaziye Bet\u00fcl \u00d6zate\u015f","raw_affiliation_strings":["Institute for Data Science &amp; Artificial Intelligence of Bo&#x011F;azi&#x00E7;i University, &#x0130;stanbul, T&#x00FC;rkiye"],"raw_orcid":"https://orcid.org/0000-0003-3254-0960","affiliations":[{"raw_affiliation_string":"Institute for Data Science &amp; Artificial Intelligence of Bo&#x011F;azi&#x00E7;i University, &#x0130;stanbul, T&#x00FC;rkiye","institution_ids":["https://openalex.org/I2799978770"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107293679","display_name":"Nehir G\u00fczelkaya","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Nehir G\u00fczelkaya","raw_affiliation_strings":["Chair of Automatic Control Engineering, Technical University of Munich, M&#x00FC;nchen, Germany"],"raw_orcid":"https://orcid.org/0009-0001-4425-8690","affiliations":[{"raw_affiliation_string":"Chair of Automatic Control Engineering, Technical University of Munich, M&#x00FC;nchen, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33902374,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"3","first_page":"2610","last_page":"2623"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11081","display_name":"Advanced Control Systems Design","score":0.3034999966621399,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11081","display_name":"Advanced Control Systems Design","score":0.3034999966621399,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12794","display_name":"Adaptive Dynamic Programming Control","score":0.0421999990940094,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.03779999911785126,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5055999755859375},{"id":"https://openalex.org/keywords/pid-controller","display_name":"PID controller","score":0.46950000524520874},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.4641999900341034},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4194999933242798},{"id":"https://openalex.org/keywords/control-system","display_name":"Control system","score":0.41190001368522644},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.40230000019073486},{"id":"https://openalex.org/keywords/supervisory-control","display_name":"Supervisory control","score":0.3828999996185303},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.32409998774528503}],"concepts":[{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.5644999742507935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5529999732971191},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5055999755859375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5055000185966492},{"id":"https://openalex.org/C47116090","wikidata":"https://www.wikidata.org/wiki/Q716829","display_name":"PID controller","level":3,"score":0.46950000524520874},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.4641999900341034},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4194999933242798},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.41190001368522644},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40230000019073486},{"id":"https://openalex.org/C92991967","wikidata":"https://www.wikidata.org/wiki/Q7644329","display_name":"Supervisory control","level":3,"score":0.3828999996185303},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3479999899864197},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.32409998774528503},{"id":"https://openalex.org/C167123822","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automatic control","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C155386361","wikidata":"https://www.wikidata.org/wiki/Q1649571","display_name":"Process control","level":3,"score":0.259799987077713},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.258899986743927},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.25380000472068787},{"id":"https://openalex.org/C107464732","wikidata":"https://www.wikidata.org/wiki/Q235781","display_name":"Adaptive control","level":3,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetci.2026.3669780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2026.3669780","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Proportional-integral-derivative":[0],"(PID)":[1],"control":[2,10,23,83,103],"is":[3,33,69,84,132],"by":[4],"far":[5],"the":[6,19,30,50,56,62,73,78,100,138,143,174,193],"most":[7],"widely":[8],"used":[9],"type":[11],"in":[12,61],"industry.":[13],"However,":[14],"for":[15,88,99],"some":[16],"systems":[17],"even":[18],"optimally":[20,159,194],"tuned":[21,160,195],"PID":[22,59,82,102,162,176,196],"system":[24,32,43,74],"can":[25],"be":[26],"unsatisfactory,":[27],"especially":[28],"when":[29,42],"underlying":[31],"nonlinear,":[34],"includes":[35],"parameter-varying":[36,116],"components":[37],"and":[38,53,118,154],"time":[39],"delays":[40],"or":[41],"dynamics":[44],"change":[45],"with":[46,65,164,198],"time.":[47],"Due":[48],"to":[49,71,108,179,187,192],"long-standing":[51],"development":[52],"readiness":[54],"of":[55,58,125,137],"infrastructure":[57],"controllers":[60,112,163,172,177],"industry,":[63],"along":[64],"cost":[66],"factors,":[67],"it":[68,148],"essential":[70],"improve":[72],"performance":[75,157,189],"without":[76],"replacing":[77],"established":[79],"structure.":[80],"Gain-scheduled":[81],"a":[85,96,127,135],"strong":[86],"solution":[87],"such":[89,113],"situations.":[90],"In":[91],"this":[92],"paper,":[93],"we":[94,146],"present":[95],"new":[97],"approach":[98],"gain-scheduled":[101,175,183],"design":[104],"using":[105],"deep":[106,128],"learning":[107,120],"learn":[109],"from":[110],"advanced":[111,170],"as":[114,134,167,169],"linear":[115],"controller":[117,197],"reinforcement":[119],"agent.":[121],"For":[122],"each":[123],"gain":[124],"PID,":[126],"artificial":[129],"neural":[130],"network":[131],"developed":[133],"function":[136],"scheduling":[139],"signals.":[140],"To":[141],"validate":[142],"proposed":[144,182],"approach,":[145],"tested":[147],"on":[149],"two":[150],"challenging":[151],"case":[152],"studies":[153],"compared":[155],"its":[156],"against":[158],"conventional":[161],"fixed":[165,199],"parameters,":[166],"well":[168],"state-of-the-art":[171],"that":[173],"aim":[178],"emulate.":[180],"The":[181],"method":[184],"provided":[185],"up":[186],"71.6%":[188],"improvement":[190],"relative":[191],"gains.":[200]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-14T00:00:00"}
