Fuzzy logic blend with PID controller for humidity process - a rule based approach
Humidity affects product quality as well as human comfort. An experimental setup for humidifying process was developed and a suitable black box model is identified for the process. A Fuzzy Logic Controller (FLC) is designed for this process with rule base based on Internal Model Control Proportional...
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| creator | Venkatesh, S. Sundaram, S. |
| description | Humidity affects product quality as well as human comfort. An experimental setup for humidifying process was developed and a suitable black box model is identified for the process. A Fuzzy Logic Controller (FLC) is designed for this process with rule base based on Internal Model Control Proportional Integral technique (IMCPI). FLC was simulated in the MATLAB environment for the humidifying process. By changing the rule base and the number of member ship functions the step response of the system was analyzed. The system showed better performance for higher number of membership functions. |
| doi_str_mv | 10.1109/ICCEET.2012.6203887 |
| format | Conference Proceeding |
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An experimental setup for humidifying process was developed and a suitable black box model is identified for the process. A Fuzzy Logic Controller (FLC) is designed for this process with rule base based on Internal Model Control Proportional Integral technique (IMCPI). FLC was simulated in the MATLAB environment for the humidifying process. By changing the rule base and the number of member ship functions the step response of the system was analyzed. 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An experimental setup for humidifying process was developed and a suitable black box model is identified for the process. A Fuzzy Logic Controller (FLC) is designed for this process with rule base based on Internal Model Control Proportional Integral technique (IMCPI). FLC was simulated in the MATLAB environment for the humidifying process. By changing the rule base and the number of member ship functions the step response of the system was analyzed. The system showed better performance for higher number of membership functions.</description><subject>Delta modulation</subject><subject>Fuzzy Logic Controller</subject><subject>Humidity</subject><subject>IMCPI</subject><subject>IP networks</subject><subject>Membership functions</subject><subject>Rule base</subject><isbn>9781467302111</isbn><isbn>1467302112</isbn><isbn>1467302120</isbn><isbn>9781467302104</isbn><isbn>1467302104</isbn><isbn>9781467302128</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1kFFLwzAUhSMiqHO_YC_3D7Tem3RJ8yh1c4WBInsfSZq6SLeWtEW6X-_AeV4Ohw8Oh8PYgjAlQv1cFsVqtUs5Ek8lR5Hn6oY9UiaVQE4cb9lcq_w_E92zed9_40UKeZ7hA_tcj-fzBE37FRzYxp8q-AnDAT7KV3DtaYht0_gIdRvhMB5DFYYJutg63_eQgIE4Nh6s6X0FprsA4w5P7K42Te_nV5-x3Xq1KzbJ9v2tLF62SdA4JJqIW61UjkjOOuRSCIfWGc2XSyNIq8texIoby8nLTGa1REsota15VaOYscVfbfDe77sYjiZO--sL4hePR09q</recordid><startdate>201203</startdate><enddate>201203</enddate><creator>Venkatesh, S.</creator><creator>Sundaram, S.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201203</creationdate><title>Fuzzy logic blend with PID controller for humidity process - a rule based approach</title><author>Venkatesh, S. ; Sundaram, S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-9112b9778001cbc02633c0bca9255a319711100d2ab21e6464f60b1069bf2df03</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Delta modulation</topic><topic>Fuzzy Logic Controller</topic><topic>Humidity</topic><topic>IMCPI</topic><topic>IP networks</topic><topic>Membership functions</topic><topic>Rule base</topic><toplevel>online_resources</toplevel><creatorcontrib>Venkatesh, S.</creatorcontrib><creatorcontrib>Sundaram, S.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Venkatesh, S.</au><au>Sundaram, S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Fuzzy logic blend with PID controller for humidity process - a rule based approach</atitle><btitle>2012 International Conference on Computing, Electronics and Electrical Technologies (ICCEET)</btitle><stitle>ICCEET</stitle><date>2012-03</date><risdate>2012</risdate><spage>526</spage><epage>529</epage><pages>526-529</pages><isbn>9781467302111</isbn><isbn>1467302112</isbn><eisbn>1467302120</eisbn><eisbn>9781467302104</eisbn><eisbn>1467302104</eisbn><eisbn>9781467302128</eisbn><abstract>Humidity affects product quality as well as human comfort. An experimental setup for humidifying process was developed and a suitable black box model is identified for the process. A Fuzzy Logic Controller (FLC) is designed for this process with rule base based on Internal Model Control Proportional Integral technique (IMCPI). FLC was simulated in the MATLAB environment for the humidifying process. By changing the rule base and the number of member ship functions the step response of the system was analyzed. The system showed better performance for higher number of membership functions.</abstract><pub>IEEE</pub><doi>10.1109/ICCEET.2012.6203887</doi><tpages>4</tpages></addata></record> |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Delta modulation Fuzzy Logic Controller Humidity IMCPI IP networks Membership functions Rule base |
| title | Fuzzy logic blend with PID controller for humidity process - a rule based approach |
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