Synthesis of Multicriteria Controller by Means of Fuzzy Logic Approach
A two-mass fuzzy control system is considered. For fuzzification process, classical both linear and nonlinear membership functions are used. To find optimal values of membership function’s parameters, genetic algorithm is used. To take into account values of both output and intermediate parameters o...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2014/758207 |
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| _version_ | 1832564579853402112 |
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| author | Andrew Lozynskyy Lyubomyr Demkiv |
| author_facet | Andrew Lozynskyy Lyubomyr Demkiv |
| author_sort | Andrew Lozynskyy |
| collection | DOAJ |
| description | A two-mass fuzzy control system is considered. For fuzzification process, classical both linear and nonlinear membership functions are used. To find optimal values of membership function’s parameters, genetic algorithm is used. To take into account values of both output and intermediate parameters of the system, a penalty function is considered. Research is conducted for the case of speed control system and displacement control system. Obtained results are compared with the case of the system with classical, crisp controller. |
| format | Article |
| id | doaj-art-f09e36be201544de8ebda908de5e2c25 |
| institution | Kabale University |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-f09e36be201544de8ebda908de5e2c252025-02-03T01:10:48ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2014-01-01201410.1155/2014/758207758207Synthesis of Multicriteria Controller by Means of Fuzzy Logic ApproachAndrew Lozynskyy0Lyubomyr Demkiv1Lviv Polytechnic National University, 12 Bandery Street, Lviv 79026, UkraineLviv Polytechnic National University, 12 Bandery Street, Lviv 79026, UkraineA two-mass fuzzy control system is considered. For fuzzification process, classical both linear and nonlinear membership functions are used. To find optimal values of membership function’s parameters, genetic algorithm is used. To take into account values of both output and intermediate parameters of the system, a penalty function is considered. Research is conducted for the case of speed control system and displacement control system. Obtained results are compared with the case of the system with classical, crisp controller.http://dx.doi.org/10.1155/2014/758207 |
| spellingShingle | Andrew Lozynskyy Lyubomyr Demkiv Synthesis of Multicriteria Controller by Means of Fuzzy Logic Approach Advances in Fuzzy Systems |
| title | Synthesis of Multicriteria Controller by Means of Fuzzy Logic Approach |
| title_full | Synthesis of Multicriteria Controller by Means of Fuzzy Logic Approach |
| title_fullStr | Synthesis of Multicriteria Controller by Means of Fuzzy Logic Approach |
| title_full_unstemmed | Synthesis of Multicriteria Controller by Means of Fuzzy Logic Approach |
| title_short | Synthesis of Multicriteria Controller by Means of Fuzzy Logic Approach |
| title_sort | synthesis of multicriteria controller by means of fuzzy logic approach |
| url | http://dx.doi.org/10.1155/2014/758207 |
| work_keys_str_mv | AT andrewlozynskyy synthesisofmulticriteriacontrollerbymeansoffuzzylogicapproach AT lyubomyrdemkiv synthesisofmulticriteriacontrollerbymeansoffuzzylogicapproach |