Fuzzy controller for mechanical systems
In many applications of motion control, the occurrence of nonlinear friction constitutes a fundamental obstacle in the design of satisfactory controlling systems. Since it is seldom possible to obtain a relatively accurate model of resistance to motion, a solution more and more often applied in prac...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on fuzzy systems 2000-10, Vol.8 (5), p.645-652 |
|---|---|
| 1. Verfasser: | |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 652 |
|---|---|
| container_issue | 5 |
| container_start_page | 645 |
| container_title | IEEE transactions on fuzzy systems |
| container_volume | 8 |
| creator | Kulczycki, P. |
| description | In many applications of motion control, the occurrence of nonlinear friction constitutes a fundamental obstacle in the design of satisfactory controlling systems. Since it is seldom possible to obtain a relatively accurate model of resistance to motion, a solution more and more often applied in practice is to introduce approaches that incorporate the inevitable imprecisions of the model in the form of uncertainties. This paper deals with the time-optimal (minimum-time) control for mechanical systems with a discontinuous and uncertain model of resistance to motion, A fuzzy approach is used in the design of suboptimal feedback controllers, convenient in practice thanks to their many advantages, especially in respect to robustness. |
| doi_str_mv | 10.1109/91.873587 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_proquest_journals_917728858</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>873587</ieee_id><sourcerecordid>2570073361</sourcerecordid><originalsourceid>FETCH-LOGICAL-c372t-6a4ef627e178871eb16b8df13bd60391ed6e4b4b70f8243c4e948cc6e2856dc83</originalsourceid><addsrcrecordid>eNp90D1PwzAQBmALgUQJDKxMEQMfQ4rPdmxnrCoKSJVYYLYS5yJSJXGxk6H99aRKxcDAdCfdozvdS8g10DkAzZ4ymGvFU61OyAwyAQmlXJyOPZU8kYrKc3IRwoZSECnoGblfDfv9Lrau671rGvRx5Xzcov3Ku9rmTRx2occ2XJKzKm8CXh1rRD5Xzx_L12T9_vK2XKwTyxXrE5kLrCRTCEprBViALHRZAS9KSXkGWEoUhSgUrTQT3ArMhLZWItOpLK3mEbmb9m69-x4w9Katg8WmyTt0QzBMc5rS8amIPPwLQSpgSqRCjPT2D924wXfjGyYDpZjW6eHw44SsdyF4rMzW123udwaoOUQ7WjNFO9qbydaI-OuOwx99lXFk</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>917728858</pqid></control><display><type>article</type><title>Fuzzy controller for mechanical systems</title><source>IEEE Electronic Library (IEL)</source><creator>Kulczycki, P.</creator><creatorcontrib>Kulczycki, P.</creatorcontrib><description>In many applications of motion control, the occurrence of nonlinear friction constitutes a fundamental obstacle in the design of satisfactory controlling systems. Since it is seldom possible to obtain a relatively accurate model of resistance to motion, a solution more and more often applied in practice is to introduce approaches that incorporate the inevitable imprecisions of the model in the form of uncertainties. This paper deals with the time-optimal (minimum-time) control for mechanical systems with a discontinuous and uncertain model of resistance to motion, A fuzzy approach is used in the design of suboptimal feedback controllers, convenient in practice thanks to their many advantages, especially in respect to robustness.</description><identifier>ISSN: 1063-6706</identifier><identifier>EISSN: 1941-0034</identifier><identifier>DOI: 10.1109/91.873587</identifier><identifier>CODEN: IEFSEV</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Adaptive control ; Control system synthesis ; Control systems ; Controllers ; Design engineering ; Feedback ; Friction ; Fuzzy ; Fuzzy control ; Fuzzy systems ; Mechanical systems ; Motion control ; Nonlinear control systems ; Obstacles ; Uncertainty</subject><ispartof>IEEE transactions on fuzzy systems, 2000-10, Vol.8 (5), p.645-652</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2000</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c372t-6a4ef627e178871eb16b8df13bd60391ed6e4b4b70f8243c4e948cc6e2856dc83</citedby><cites>FETCH-LOGICAL-c372t-6a4ef627e178871eb16b8df13bd60391ed6e4b4b70f8243c4e948cc6e2856dc83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/873587$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,777,781,793,27905,27906,54739</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/873587$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Kulczycki, P.</creatorcontrib><title>Fuzzy controller for mechanical systems</title><title>IEEE transactions on fuzzy systems</title><addtitle>TFUZZ</addtitle><description>In many applications of motion control, the occurrence of nonlinear friction constitutes a fundamental obstacle in the design of satisfactory controlling systems. Since it is seldom possible to obtain a relatively accurate model of resistance to motion, a solution more and more often applied in practice is to introduce approaches that incorporate the inevitable imprecisions of the model in the form of uncertainties. This paper deals with the time-optimal (minimum-time) control for mechanical systems with a discontinuous and uncertain model of resistance to motion, A fuzzy approach is used in the design of suboptimal feedback controllers, convenient in practice thanks to their many advantages, especially in respect to robustness.</description><subject>Adaptive control</subject><subject>Control system synthesis</subject><subject>Control systems</subject><subject>Controllers</subject><subject>Design engineering</subject><subject>Feedback</subject><subject>Friction</subject><subject>Fuzzy</subject><subject>Fuzzy control</subject><subject>Fuzzy systems</subject><subject>Mechanical systems</subject><subject>Motion control</subject><subject>Nonlinear control systems</subject><subject>Obstacles</subject><subject>Uncertainty</subject><issn>1063-6706</issn><issn>1941-0034</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp90D1PwzAQBmALgUQJDKxMEQMfQ4rPdmxnrCoKSJVYYLYS5yJSJXGxk6H99aRKxcDAdCfdozvdS8g10DkAzZ4ymGvFU61OyAwyAQmlXJyOPZU8kYrKc3IRwoZSECnoGblfDfv9Lrau671rGvRx5Xzcov3Ku9rmTRx2occ2XJKzKm8CXh1rRD5Xzx_L12T9_vK2XKwTyxXrE5kLrCRTCEprBViALHRZAS9KSXkGWEoUhSgUrTQT3ArMhLZWItOpLK3mEbmb9m69-x4w9Katg8WmyTt0QzBMc5rS8amIPPwLQSpgSqRCjPT2D924wXfjGyYDpZjW6eHw44SsdyF4rMzW123udwaoOUQ7WjNFO9qbydaI-OuOwx99lXFk</recordid><startdate>20001001</startdate><enddate>20001001</enddate><creator>Kulczycki, P.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>RIA</scope><scope>RIE</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><scope>7SP</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20001001</creationdate><title>Fuzzy controller for mechanical systems</title><author>Kulczycki, P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c372t-6a4ef627e178871eb16b8df13bd60391ed6e4b4b70f8243c4e948cc6e2856dc83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Adaptive control</topic><topic>Control system synthesis</topic><topic>Control systems</topic><topic>Controllers</topic><topic>Design engineering</topic><topic>Feedback</topic><topic>Friction</topic><topic>Fuzzy</topic><topic>Fuzzy control</topic><topic>Fuzzy systems</topic><topic>Mechanical systems</topic><topic>Motion control</topic><topic>Nonlinear control systems</topic><topic>Obstacles</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kulczycki, P.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</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><collection>Electronics & Communications Abstracts</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on fuzzy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kulczycki, P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fuzzy controller for mechanical systems</atitle><jtitle>IEEE transactions on fuzzy systems</jtitle><stitle>TFUZZ</stitle><date>2000-10-01</date><risdate>2000</risdate><volume>8</volume><issue>5</issue><spage>645</spage><epage>652</epage><pages>645-652</pages><issn>1063-6706</issn><eissn>1941-0034</eissn><coden>IEFSEV</coden><abstract>In many applications of motion control, the occurrence of nonlinear friction constitutes a fundamental obstacle in the design of satisfactory controlling systems. Since it is seldom possible to obtain a relatively accurate model of resistance to motion, a solution more and more often applied in practice is to introduce approaches that incorporate the inevitable imprecisions of the model in the form of uncertainties. This paper deals with the time-optimal (minimum-time) control for mechanical systems with a discontinuous and uncertain model of resistance to motion, A fuzzy approach is used in the design of suboptimal feedback controllers, convenient in practice thanks to their many advantages, especially in respect to robustness.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/91.873587</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1063-6706 |
| ispartof | IEEE transactions on fuzzy systems, 2000-10, Vol.8 (5), p.645-652 |
| issn | 1063-6706 1941-0034 |
| language | eng |
| recordid | cdi_proquest_journals_917728858 |
| source | IEEE Electronic Library (IEL) |
| subjects | Adaptive control Control system synthesis Control systems Controllers Design engineering Feedback Friction Fuzzy Fuzzy control Fuzzy systems Mechanical systems Motion control Nonlinear control systems Obstacles Uncertainty |
| title | Fuzzy controller for mechanical systems |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T22%3A34%3A56IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Fuzzy%20controller%20for%20mechanical%20systems&rft.jtitle=IEEE%20transactions%20on%20fuzzy%20systems&rft.au=Kulczycki,%20P.&rft.date=2000-10-01&rft.volume=8&rft.issue=5&rft.spage=645&rft.epage=652&rft.pages=645-652&rft.issn=1063-6706&rft.eissn=1941-0034&rft.coden=IEFSEV&rft_id=info:doi/10.1109/91.873587&rft_dat=%3Cproquest_RIE%3E2570073361%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=917728858&rft_id=info:pmid/&rft_ieee_id=873587&rfr_iscdi=true |