Fuzzy logic for constant force control of end milling
The machining condition usually has significant variation resulting from the change of cutting depth and the intrinsic property of the workpiece. In order to maintain the performance of a classical proportional integral derivative control system, the tool life and machining quality, conservative fee...
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| Veröffentlicht in: | IEEE transactions on industrial electronics (1982) 1999-02, Vol.46 (1), p.169-176 |
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| container_title | IEEE transactions on industrial electronics (1982) |
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| creator | HUANG, S.-J SHY, C.-Y |
| description | The machining condition usually has significant variation resulting from the change of cutting depth and the intrinsic property of the workpiece. In order to maintain the performance of a classical proportional integral derivative control system, the tool life and machining quality, conservative feedrate, and cutting depth change are prespecified as the limitations of computer numerically controlled operators. Therefore, constant cutting force control is proposed as a useful approach for increasing the metal removal rate and the tool life. However, the model-based controller cannot handle the nonlinearity of a force control system due to cutting condition variations. Here, a fuzzy controller with learning ability was employed to improve both the system performance and the adaptability. This control approach vias implemented on a retrofit old-fashioned milling machine for the end milling process. The experimental results show that this control strategy has smooth feedrate and good cutting force dynamic responses. |
| doi_str_mv | 10.1109/41.744408 |
| format | Article |
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In order to maintain the performance of a classical proportional integral derivative control system, the tool life and machining quality, conservative feedrate, and cutting depth change are prespecified as the limitations of computer numerically controlled operators. Therefore, constant cutting force control is proposed as a useful approach for increasing the metal removal rate and the tool life. However, the model-based controller cannot handle the nonlinearity of a force control system due to cutting condition variations. Here, a fuzzy controller with learning ability was employed to improve both the system performance and the adaptability. This control approach vias implemented on a retrofit old-fashioned milling machine for the end milling process. The experimental results show that this control strategy has smooth feedrate and good cutting force dynamic responses.</description><identifier>ISSN: 0278-0046</identifier><identifier>EISSN: 1557-9948</identifier><identifier>DOI: 10.1109/41.744408</identifier><identifier>CODEN: ITIED6</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Applied sciences ; Control systems ; Cutting force ; Cutting parameters ; Dynamical systems ; Electrical engineering. Electrical power engineering ; Electrical machines ; End milling ; Exact sciences and technology ; Force control ; Fuzzy control ; Fuzzy logic ; Machining ; Mathematical models ; Milling ; Nonlinear control systems ; PD control ; Pi control ; Proportional control ; Regulation and control ; Tool life</subject><ispartof>IEEE transactions on industrial electronics (1982), 1999-02, Vol.46 (1), p.169-176</ispartof><rights>1999 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c400t-df5173f019bbd9d6b91e64dbcefc06ab3083013588d524a8af21546e09f0e7533</citedby><cites>FETCH-LOGICAL-c400t-df5173f019bbd9d6b91e64dbcefc06ab3083013588d524a8af21546e09f0e7533</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/744408$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/744408$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=1694504$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>HUANG, S.-J</creatorcontrib><creatorcontrib>SHY, C.-Y</creatorcontrib><title>Fuzzy logic for constant force control of end milling</title><title>IEEE transactions on industrial electronics (1982)</title><addtitle>TIE</addtitle><description>The machining condition usually has significant variation resulting from the change of cutting depth and the intrinsic property of the workpiece. In order to maintain the performance of a classical proportional integral derivative control system, the tool life and machining quality, conservative feedrate, and cutting depth change are prespecified as the limitations of computer numerically controlled operators. Therefore, constant cutting force control is proposed as a useful approach for increasing the metal removal rate and the tool life. However, the model-based controller cannot handle the nonlinearity of a force control system due to cutting condition variations. Here, a fuzzy controller with learning ability was employed to improve both the system performance and the adaptability. This control approach vias implemented on a retrofit old-fashioned milling machine for the end milling process. The experimental results show that this control strategy has smooth feedrate and good cutting force dynamic responses.</description><subject>Applied sciences</subject><subject>Control systems</subject><subject>Cutting force</subject><subject>Cutting parameters</subject><subject>Dynamical systems</subject><subject>Electrical engineering. Electrical power engineering</subject><subject>Electrical machines</subject><subject>End milling</subject><subject>Exact sciences and technology</subject><subject>Force control</subject><subject>Fuzzy control</subject><subject>Fuzzy logic</subject><subject>Machining</subject><subject>Mathematical models</subject><subject>Milling</subject><subject>Nonlinear control systems</subject><subject>PD control</subject><subject>Pi control</subject><subject>Proportional control</subject><subject>Regulation and control</subject><subject>Tool life</subject><issn>0278-0046</issn><issn>1557-9948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1999</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqF0T1LA0EQBuBFFIzRwtbqClEsLs7c7WcpwagQsNH62NvbDSeb27h7KZJfb8IF7Uw1DPPMy8AQco0wQQT1SHEiKKUgT8gIGRO5UlSekhEUQuYAlJ-Ti5S-AJAyZCPCZuvtdpP5sGhN5kLMTOhSr7t-3xi7b_sYfBZcZrsmW7bet93ikpw57ZO9OtQx-Zw9f0xf8_n7y9v0aZ4bCtDnjWMoSgeo6rpRDa8VWk6b2lhngOu6BFkClkzKhhVUS-0KZJRbUA6sYGU5JvdD7iqG77VNfbVsk7He686GdaoUKoXAFe7k3b-yUIXiXNDjUBYKOZXHIVeCYil28GGAJoaUonXVKrZLHTcVQrV_SkWxGp6ys7eHUJ2M9i7qzrTpb4ErymB_5M3AWmvt7_SQ8QMAJJFo</recordid><startdate>19990201</startdate><enddate>19990201</enddate><creator>HUANG, S.-J</creator><creator>SHY, C.-Y</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>RIA</scope><scope>RIE</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><scope>7TB</scope><scope>FR3</scope><scope>F28</scope></search><sort><creationdate>19990201</creationdate><title>Fuzzy logic for constant force control of end milling</title><author>HUANG, S.-J ; SHY, C.-Y</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c400t-df5173f019bbd9d6b91e64dbcefc06ab3083013588d524a8af21546e09f0e7533</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Applied sciences</topic><topic>Control systems</topic><topic>Cutting force</topic><topic>Cutting parameters</topic><topic>Dynamical systems</topic><topic>Electrical engineering. Electrical power engineering</topic><topic>Electrical machines</topic><topic>End milling</topic><topic>Exact sciences and technology</topic><topic>Force control</topic><topic>Fuzzy control</topic><topic>Fuzzy logic</topic><topic>Machining</topic><topic>Mathematical models</topic><topic>Milling</topic><topic>Nonlinear control systems</topic><topic>PD control</topic><topic>Pi control</topic><topic>Proportional control</topic><topic>Regulation and control</topic><topic>Tool life</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>HUANG, S.-J</creatorcontrib><creatorcontrib>SHY, C.-Y</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Engineering Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><jtitle>IEEE transactions on industrial electronics (1982)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>HUANG, S.-J</au><au>SHY, C.-Y</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fuzzy logic for constant force control of end milling</atitle><jtitle>IEEE transactions on industrial electronics (1982)</jtitle><stitle>TIE</stitle><date>1999-02-01</date><risdate>1999</risdate><volume>46</volume><issue>1</issue><spage>169</spage><epage>176</epage><pages>169-176</pages><issn>0278-0046</issn><eissn>1557-9948</eissn><coden>ITIED6</coden><abstract>The machining condition usually has significant variation resulting from the change of cutting depth and the intrinsic property of the workpiece. In order to maintain the performance of a classical proportional integral derivative control system, the tool life and machining quality, conservative feedrate, and cutting depth change are prespecified as the limitations of computer numerically controlled operators. Therefore, constant cutting force control is proposed as a useful approach for increasing the metal removal rate and the tool life. However, the model-based controller cannot handle the nonlinearity of a force control system due to cutting condition variations. Here, a fuzzy controller with learning ability was employed to improve both the system performance and the adaptability. This control approach vias implemented on a retrofit old-fashioned milling machine for the end milling process. The experimental results show that this control strategy has smooth feedrate and good cutting force dynamic responses.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/41.744408</doi><tpages>8</tpages></addata></record> |
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| ispartof | IEEE transactions on industrial electronics (1982), 1999-02, Vol.46 (1), p.169-176 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Applied sciences Control systems Cutting force Cutting parameters Dynamical systems Electrical engineering. Electrical power engineering Electrical machines End milling Exact sciences and technology Force control Fuzzy control Fuzzy logic Machining Mathematical models Milling Nonlinear control systems PD control Pi control Proportional control Regulation and control Tool life |
| title | Fuzzy logic for constant force control of end milling |
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