{"id":"https://openalex.org/W2002040799","doi":"https://doi.org/10.1109/cca.2013.6662867","title":"Successive difference method for steady state detection in univariate system","display_name":"Successive difference method for steady state detection in univariate system","publication_year":2013,"publication_date":"2013-08-01","ids":{"openalex":"https://openalex.org/W2002040799","doi":"https://doi.org/10.1109/cca.2013.6662867","mag":"2002040799"},"language":"en","primary_location":{"id":"doi:10.1109/cca.2013.6662867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cca.2013.6662867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Control Applications (CCA)","raw_type":"proceedings-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/A5030924332","display_name":"Manoj K. Gootam","orcid":null},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Manoj K. Gootam","raw_affiliation_strings":["Chemical Engineering Department, Indian Institute of Technology, Madras, India","Chem. Eng. Dept., Indian Inst. of Technol., Madras, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Chemical Engineering Department, Indian Institute of Technology, Madras, India","institution_ids":["https://openalex.org/I24676775"]},{"raw_affiliation_string":"Chem. Eng. Dept., Indian Inst. of Technol., Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084722124","display_name":"Nandkishor Kubal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141895","display_name":"Resource Optimization Initiative","ror":"https://ror.org/0417mky81","country_code":"IN","type":"nonprofit","lineage":["https://openalex.org/I4210141895"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nandkishor Kubal","raw_affiliation_strings":["Control and Optimization Research department, ABB GISL, Bangalore, India","Control & Optimization Res. Dept, ABB GISL, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Control and Optimization Research department, ABB GISL, Bangalore, India","institution_ids":["https://openalex.org/I4210141895"]},{"raw_affiliation_string":"Control & Optimization Res. Dept, ABB GISL, Bangalore, India","institution_ids":["https://openalex.org/I4210141895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070616572","display_name":"Ulaganathan Nallasivam","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141895","display_name":"Resource Optimization Initiative","ror":"https://ror.org/0417mky81","country_code":"IN","type":"nonprofit","lineage":["https://openalex.org/I4210141895"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ulaganathan Nallasivam","raw_affiliation_strings":["Control and Optimization Research department, ABB GISL, Bangalore, India","Control & Optimization Res. Dept, ABB GISL, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Control and Optimization Research department, ABB GISL, Bangalore, India","institution_ids":["https://openalex.org/I4210141895"]},{"raw_affiliation_string":"Control & Optimization Res. Dept, ABB GISL, Bangalore, India","institution_ids":["https://openalex.org/I4210141895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5030924332"],"corresponding_institution_ids":["https://openalex.org/I24676775"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08379781,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"912","last_page":"916"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9968000054359436,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9968000054359436,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/univariate","display_name":"Univariate","score":0.8303583860397339},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.703382134437561},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.5627939701080322},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5562722086906433},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49708274006843567},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4858236312866211},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4414728879928589},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4141325354576111},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38787734508514404},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.2698647677898407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21664324402809143},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1678846776485443}],"concepts":[{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.8303583860397339},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.703382134437561},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.5627939701080322},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5562722086906433},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49708274006843567},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4858236312866211},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4414728879928589},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4141325354576111},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38787734508514404},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.2698647677898407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21664324402809143},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1678846776485443},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cca.2013.6662867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cca.2013.6662867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Control Applications (CCA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1518368624","https://openalex.org/W1967085503","https://openalex.org/W2035209205","https://openalex.org/W2042696696","https://openalex.org/W2060570856","https://openalex.org/W2070274441","https://openalex.org/W2109567225","https://openalex.org/W2109606373","https://openalex.org/W4302557032"],"related_works":["https://openalex.org/W1828158523","https://openalex.org/W2047547195","https://openalex.org/W204175656","https://openalex.org/W2911841387","https://openalex.org/W2803255289","https://openalex.org/W1512294453","https://openalex.org/W1993992974","https://openalex.org/W2550734047","https://openalex.org/W2176526134","https://openalex.org/W3134489511"],"abstract_inverted_index":{"The":[0,47,131],"use":[1,37],"of":[2,38,41,100,124,133],"online":[3],"data":[4,15,128],"for":[5,30],"steady-state":[6],"detection":[7],"is":[8,33,49,57,119,136,161,167],"required":[9],"to":[10,61,96],"solve":[11],"problems":[12],"like":[13,90],"statistical":[14],"reconciliation,":[16],"real":[17],"time":[18,42,74,126],"optimization":[19],"and":[20,164],"controller":[21],"performance":[22,99,110,132,166],"monitoring.":[23],"In":[24,94],"this":[25,69,134],"paper,":[26],"a":[27,104,122],"new":[28],"method":[29,48,70,135,160],"univariate":[31],"system":[32],"proposed,":[34],"which":[35,55],"makes":[36],"successive":[39],"differences":[40],"series":[43,127],"(single":[44],"variate)":[45],"data.":[46],"simple":[50],"because":[51],"the":[52,85,98,101,114,139,148,155,170],"parameters":[53],"on":[54,108],"it":[56,76],"based":[58,107],"are":[59,65,145],"easy":[60],"tune":[62],"as":[63,75,84],"they":[64],"rather":[66],"intuitive.":[67],"Also":[68],"needs":[71],"less":[72],"computation":[73],"does":[77],"not":[78],"involve":[79],"any":[80],"model":[81],"fitting":[82],"exercise":[83],"case":[86],"with":[87,138],"other":[88],"methods":[89,143],"polynomial":[91],"interpolation":[92],"technique.":[93],"order":[95],"assess":[97],"above":[102],"method,":[103,157],"comparison":[105],"analysis":[106,152],"its":[109,165],"in":[111,121,147],"accurately":[112],"detecting":[113],"steady":[115],"state":[116],"part":[117],"that":[118,144,154],"present":[120],"set":[123],"industrial":[125],"was":[129],"performed.":[130],"compared":[137],"three":[140,172],"best":[141],"existing":[142,171],"available":[146],"current":[149],"literature.":[150],"This":[151],"showed":[153],"proposed":[156],"Successive":[158],"Difference":[159],"most":[162],"robust":[163],"better":[168],"than":[169],"methods.":[173]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}