Fuzzy logic in a blackboard system for controlling plasma deposition processes
A blackboard system, ARBS, has been used to control a plasma processing unit, which is used for depositing coatings on the surface of electronic or mechanical components. Previous applications of ARBS have been based on crisp logic, but fuzzy logic was added in this study for plasma deposition contr...
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Veröffentlicht in: | Artificial intelligence in engineering 1998-07, Vol.12 (3), p.253-260 |
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creator | Hopgood, A.A. Phillips, H.J. Picton, P.D. Braithwaite, N.St.J. |
description | A blackboard system, ARBS, has been used to control a plasma processing unit, which is used for depositing coatings on the surface of electronic or mechanical components. Previous applications of ARBS have been based on crisp logic, but fuzzy logic was added in this study for plasma deposition control. Fuzzy rules have been introduced into ARBS without changing either the rule syntax or the existing inference engines, thereby demonstrating the flexibility of the software. Consequently crisp and fuzzy rules can coexist within a single knowledge source (i.e. module).
An efficient technique for defuzzification has been employed in which the membership functions are replaced by Dirac delta functions. The technique is equivalent to standard methods of defuzzification, without loss of precision or accuracy, but with a reduced number of calculations. Multi-variable control of DC-bias (an electrical parameter) by automatic adjustment of pressure and RF (radio frequency) electrical power is demonstrated. |
doi_str_mv | 10.1016/S0954-1810(97)00024-1 |
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An efficient technique for defuzzification has been employed in which the membership functions are replaced by Dirac delta functions. The technique is equivalent to standard methods of defuzzification, without loss of precision or accuracy, but with a reduced number of calculations. Multi-variable control of DC-bias (an electrical parameter) by automatic adjustment of pressure and RF (radio frequency) electrical power is demonstrated.</description><identifier>ISSN: 0954-1810</identifier><identifier>DOI: 10.1016/S0954-1810(97)00024-1</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Applied sciences ; ARBS ; Artificial intelligence ; blackboard system ; Computer science; control theory; systems ; Control theory. Systems ; defuzzification ; Exact sciences and technology ; fuzzy logic ; Learning and adaptive systems ; multi-variable control ; plasma processing ; Process control. Computer integrated manufacturing ; rules</subject><ispartof>Artificial intelligence in engineering, 1998-07, Vol.12 (3), p.253-260</ispartof><rights>1998</rights><rights>1998 INIST-CNRS</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c367t-839c0bf8f89a980758efc0960ebec724c6915df60f8717eb84e93baae628fc653</citedby><cites>FETCH-LOGICAL-c367t-839c0bf8f89a980758efc0960ebec724c6915df60f8717eb84e93baae628fc653</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=2237354$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Hopgood, A.A.</creatorcontrib><creatorcontrib>Phillips, H.J.</creatorcontrib><creatorcontrib>Picton, P.D.</creatorcontrib><creatorcontrib>Braithwaite, N.St.J.</creatorcontrib><title>Fuzzy logic in a blackboard system for controlling plasma deposition processes</title><title>Artificial intelligence in engineering</title><description>A blackboard system, ARBS, has been used to control a plasma processing unit, which is used for depositing coatings on the surface of electronic or mechanical components. Previous applications of ARBS have been based on crisp logic, but fuzzy logic was added in this study for plasma deposition control. Fuzzy rules have been introduced into ARBS without changing either the rule syntax or the existing inference engines, thereby demonstrating the flexibility of the software. Consequently crisp and fuzzy rules can coexist within a single knowledge source (i.e. module).
An efficient technique for defuzzification has been employed in which the membership functions are replaced by Dirac delta functions. The technique is equivalent to standard methods of defuzzification, without loss of precision or accuracy, but with a reduced number of calculations. Multi-variable control of DC-bias (an electrical parameter) by automatic adjustment of pressure and RF (radio frequency) electrical power is demonstrated.</description><subject>Applied sciences</subject><subject>ARBS</subject><subject>Artificial intelligence</subject><subject>blackboard system</subject><subject>Computer science; control theory; systems</subject><subject>Control theory. Systems</subject><subject>defuzzification</subject><subject>Exact sciences and technology</subject><subject>fuzzy logic</subject><subject>Learning and adaptive systems</subject><subject>multi-variable control</subject><subject>plasma processing</subject><subject>Process control. Computer integrated manufacturing</subject><subject>rules</subject><issn>0954-1810</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1998</creationdate><recordtype>article</recordtype><recordid>eNqFkE1LAzEQhvegYP34CUIOInqoJvuV5CQiVoWiB_UcsrOTEk03NbMV2l_v1kqvnoaZed55mTfLTgW_ElzU169cV-VYKMEvtLzknOdDt5eNduOD7JDoY1goLsQoe54s1-sVC3HmgfmOWdYEC59NtKlltKIe58zFxCB2fYoh-G7GFsHS3LIWF5F872PHFikCEiEdZ_vOBsKTv3qUvU_u3-4ex9OXh6e72-kYilr2Y1Vo4I1TTmmrFZeVQgdc1xwbBJmXUGtRta7mTkkhsVEl6qKxFutcOair4ig7394dnL-WSL2ZewIMwXYYl2RyWeVKlvkAVlsQUiRK6Mwi-blNKyO42SRmfhMzm2iMluY3MSMG3dmfgSWwwSXbgaedOM8LWVTlgN1sMRye_faYDIHHDrD1CaE3bfT_GP0AR9CCpw</recordid><startdate>19980701</startdate><enddate>19980701</enddate><creator>Hopgood, A.A.</creator><creator>Phillips, H.J.</creator><creator>Picton, P.D.</creator><creator>Braithwaite, N.St.J.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>19980701</creationdate><title>Fuzzy logic in a blackboard system for controlling plasma deposition processes</title><author>Hopgood, A.A. ; Phillips, H.J. ; Picton, P.D. ; Braithwaite, N.St.J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c367t-839c0bf8f89a980758efc0960ebec724c6915df60f8717eb84e93baae628fc653</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1998</creationdate><topic>Applied sciences</topic><topic>ARBS</topic><topic>Artificial intelligence</topic><topic>blackboard system</topic><topic>Computer science; control theory; systems</topic><topic>Control theory. Systems</topic><topic>defuzzification</topic><topic>Exact sciences and technology</topic><topic>fuzzy logic</topic><topic>Learning and adaptive systems</topic><topic>multi-variable control</topic><topic>plasma processing</topic><topic>Process control. Computer integrated manufacturing</topic><topic>rules</topic><toplevel>online_resources</toplevel><creatorcontrib>Hopgood, A.A.</creatorcontrib><creatorcontrib>Phillips, H.J.</creatorcontrib><creatorcontrib>Picton, P.D.</creatorcontrib><creatorcontrib>Braithwaite, N.St.J.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Artificial intelligence in engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hopgood, A.A.</au><au>Phillips, H.J.</au><au>Picton, P.D.</au><au>Braithwaite, N.St.J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fuzzy logic in a blackboard system for controlling plasma deposition processes</atitle><jtitle>Artificial intelligence in engineering</jtitle><date>1998-07-01</date><risdate>1998</risdate><volume>12</volume><issue>3</issue><spage>253</spage><epage>260</epage><pages>253-260</pages><issn>0954-1810</issn><abstract>A blackboard system, ARBS, has been used to control a plasma processing unit, which is used for depositing coatings on the surface of electronic or mechanical components. Previous applications of ARBS have been based on crisp logic, but fuzzy logic was added in this study for plasma deposition control. Fuzzy rules have been introduced into ARBS without changing either the rule syntax or the existing inference engines, thereby demonstrating the flexibility of the software. Consequently crisp and fuzzy rules can coexist within a single knowledge source (i.e. module).
An efficient technique for defuzzification has been employed in which the membership functions are replaced by Dirac delta functions. The technique is equivalent to standard methods of defuzzification, without loss of precision or accuracy, but with a reduced number of calculations. Multi-variable control of DC-bias (an electrical parameter) by automatic adjustment of pressure and RF (radio frequency) electrical power is demonstrated.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/S0954-1810(97)00024-1</doi><tpages>8</tpages></addata></record> |
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subjects | Applied sciences ARBS Artificial intelligence blackboard system Computer science control theory systems Control theory. Systems defuzzification Exact sciences and technology fuzzy logic Learning and adaptive systems multi-variable control plasma processing Process control. Computer integrated manufacturing rules |
title | Fuzzy logic in a blackboard system for controlling plasma deposition processes |
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