A fuzzy-genetic approach for automatic tuning of a PID controller
A novel method employing fuzzy logic and a genetic algorithm for automatic tuning of a Proportional Integral Derivative (PID) controller is presented. The technique adopted is based on the theory of dead-beat control. A fuzzy logic technique has been used to predict the controller output and the cri...
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| creator | Chakraborty, U.K. Bandyopadhyay, R. Patranabis, D. |
| description | A novel method employing fuzzy logic and a genetic algorithm for automatic tuning of a Proportional Integral Derivative (PID) controller is presented. The technique adopted is based on the theory of dead-beat control. A fuzzy logic technique has been used to predict the controller output and the crisp consequent values of the rulebase on the Takagi-Sugeno model are optimized using a genetic algorithm. The proposition is an extension of the work by R. Bandyopadhyay and D. Patranabis (2001), where the rulebase was prepared based on the knowledge of process experts. Significant improvement has been obtained using a genetic algorithm by optimizing the crisp consequent values of the rulebase. As can be seen from the simulated results, the method shows substantial improvement over the controller tuned with the Ziegler-Nichols formula (J.G. Ziegler and N.B. Nichols, 1942) and the PID controller proposed by Bandyopadhyay and Patranabis. |
| doi_str_mv | 10.1109/ITI.2001.938034 |
| format | Conference Proceeding |
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Nichols, 1942) and the PID controller proposed by Bandyopadhyay and Patranabis.</description><subject>Automatic control</subject><subject>Error correction</subject><subject>Genetic algorithms</subject><subject>Instruments</subject><subject>Logic</subject><subject>PD control</subject><subject>Pi control</subject><subject>Proportional control</subject><subject>Sampling methods</subject><subject>Three-term control</subject><issn>1330-1012</issn><isbn>9789539676931</isbn><isbn>9539676932</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2001</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj8tqwzAQAAVtoSH1udCTfsDuSitb2qNJHzEE2kN6Dqq0Tg2Obfw4JF9fSnoamMPACPGoIFMK6LnaV5kGUBmhAzQ3IiHrKEcqbEGobsVKIUKqQOl7kUxT8w2gwRGSWomylPVyuZzTI3c8N0H6YRh7H35k3Y_SL3N_8n96XrqmO8q-ll5-Vi8y9N089m3L44O4q307cfLPtfh6e91vtunu473alLu0UdbMaZHXzMZYiAXnOfmINrLlYBBMbmsNpEgxuOicDtHkMbBBHRxxRNLG4Fo8XbsNMx-GsTn58Xy4PuMv7o1JSw</recordid><startdate>2001</startdate><enddate>2001</enddate><creator>Chakraborty, U.K.</creator><creator>Bandyopadhyay, R.</creator><creator>Patranabis, D.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2001</creationdate><title>A fuzzy-genetic approach for automatic tuning of a PID controller</title><author>Chakraborty, U.K. ; Bandyopadhyay, R. ; Patranabis, D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i174t-65fee4470d6e559ad37de7ec430457f209191e08d882cd45dce432c89ed392443</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2001</creationdate><topic>Automatic control</topic><topic>Error correction</topic><topic>Genetic algorithms</topic><topic>Instruments</topic><topic>Logic</topic><topic>PD control</topic><topic>Pi control</topic><topic>Proportional control</topic><topic>Sampling methods</topic><topic>Three-term control</topic><toplevel>online_resources</toplevel><creatorcontrib>Chakraborty, U.K.</creatorcontrib><creatorcontrib>Bandyopadhyay, R.</creatorcontrib><creatorcontrib>Patranabis, D.</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>Chakraborty, U.K.</au><au>Bandyopadhyay, R.</au><au>Patranabis, D.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A fuzzy-genetic approach for automatic tuning of a PID controller</atitle><btitle>Proceedings of the 23rd International Conference on Information Technology Interfaces, 2001. ITI 2001</btitle><stitle>ITI</stitle><date>2001</date><risdate>2001</risdate><spage>305</spage><epage>312 vol.1</epage><pages>305-312 vol.1</pages><issn>1330-1012</issn><isbn>9789539676931</isbn><isbn>9539676932</isbn><abstract>A novel method employing fuzzy logic and a genetic algorithm for automatic tuning of a Proportional Integral Derivative (PID) controller is presented. The technique adopted is based on the theory of dead-beat control. A fuzzy logic technique has been used to predict the controller output and the crisp consequent values of the rulebase on the Takagi-Sugeno model are optimized using a genetic algorithm. The proposition is an extension of the work by R. Bandyopadhyay and D. Patranabis (2001), where the rulebase was prepared based on the knowledge of process experts. Significant improvement has been obtained using a genetic algorithm by optimizing the crisp consequent values of the rulebase. As can be seen from the simulated results, the method shows substantial improvement over the controller tuned with the Ziegler-Nichols formula (J.G. Ziegler and N.B. Nichols, 1942) and the PID controller proposed by Bandyopadhyay and Patranabis.</abstract><pub>IEEE</pub><doi>10.1109/ITI.2001.938034</doi></addata></record> |
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| identifier | ISSN: 1330-1012 |
| ispartof | Proceedings of the 23rd International Conference on Information Technology Interfaces, 2001. ITI 2001, 2001, p.305-312 vol.1 |
| issn | 1330-1012 |
| language | eng |
| recordid | cdi_ieee_primary_938034 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Automatic control Error correction Genetic algorithms Instruments Logic PD control Pi control Proportional control Sampling methods Three-term control |
| title | A fuzzy-genetic approach for automatic tuning of a PID controller |
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