A new adaptive hybrid controller for vibration control of a vehicle seat suspension featuring MR damper
This paper presents a new hybrid controller which is a combination of three control schemes: fuzzy neural control, PI control and sliding mode control. The interval type 2 fuzzy model featuring updated rules via online is used in this study and in order to support the fuzzy model, a granular cluster...
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| Veröffentlicht in: | Journal of vibration and control 2017-12, Vol.23 (20), p.3392-3413 |
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| container_title | Journal of vibration and control |
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| creator | Phu, Do Xuan Choi, Sang-Min Choi, Seung-Bok |
| description | This paper presents a new hybrid controller which is a combination of three control schemes: fuzzy neural control, PI control and sliding mode control. The interval type 2 fuzzy model featuring updated rules via online is used in this study and in order to support the fuzzy model, a granular clustering method is applied to find groups of data related to the initial fuzzy rule. Then the output for fuzzy model is used for the PI-sliding mode controller. The combination of PI and sliding mode controls is carried out by H-infinity technique method which is rely on the modified Riccati-like equation. After developing the mathematical model, the proposed controller is applied to vibration control of a vehicle seat suspension featuring magneto-rheological (MR) damper. In order to demonstrate the effectiveness of the proposed controller, two different excitations of bump and random signals are adopted and corresponding vibration control performances are evaluated. It is demonstrated through both simulation and experiment that the proposed controller can provide much better than vibration control performance compared with the conventional controllers showing more robust stability. |
| doi_str_mv | 10.1177/1077546316629597 |
| format | Article |
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It is demonstrated through both simulation and experiment that the proposed controller can provide much better than vibration control performance compared with the conventional controllers showing more robust stability.</description><subject>Adaptive control</subject><subject>Artificial neural networks</subject><subject>Clustering</subject><subject>Computer simulation</subject><subject>Control stability</subject><subject>Controllers</subject><subject>Fuzzy control</subject><subject>Fuzzy logic</subject><subject>Neural networks</subject><subject>Random signals</subject><subject>Rheological properties</subject><subject>Robust control</subject><subject>Robustness (mathematics)</subject><subject>Sliding mode control</subject><subject>Vibration</subject><subject>Vibration control</subject><issn>1077-5463</issn><issn>1741-2986</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp1UM1LwzAUD6LgnN49BjxX85q2aY5jqBMmgui5pOnLltE1NWkn--_NmIIIXt4Hv4_H-xFyDewWQIg7YELkWcGhKFKZS3FCJiAySFJZFqdxjnBywM_JRQgbxliWAZuQ1Yx2-ElVo_rB7pCu97W3DdWuG7xrW_TUOE93tvZqsK77AagzVNEdrq1ukQZUAw1j6LELB5KJ--htt6LPr7RR2x79JTkzqg149d2n5P3h_m2-SJYvj0_z2TLRXORDEouSNS9rDqlIc2W0MBJ1ylHXTVE3mmudZoxxxXn8TJhGQl7WAqTGnEXllNwcfXvvPkYMQ7Vxo-_iyQpkyQQwAIgsdmRp70LwaKre263y-wpYdYiz-htnlCRHSVAr_GX6H_8LE751Yg</recordid><startdate>20171201</startdate><enddate>20171201</enddate><creator>Phu, Do Xuan</creator><creator>Choi, Sang-Min</creator><creator>Choi, Seung-Bok</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20171201</creationdate><title>A new adaptive hybrid controller for vibration control of a vehicle seat suspension featuring MR damper</title><author>Phu, Do Xuan ; Choi, Sang-Min ; Choi, Seung-Bok</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-375a9b38b312725afc7f9ec23ecbd6bdc3cc24003a332987fd9158b719ce509b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adaptive control</topic><topic>Artificial neural networks</topic><topic>Clustering</topic><topic>Computer simulation</topic><topic>Control stability</topic><topic>Controllers</topic><topic>Fuzzy control</topic><topic>Fuzzy logic</topic><topic>Neural networks</topic><topic>Random signals</topic><topic>Rheological properties</topic><topic>Robust control</topic><topic>Robustness (mathematics)</topic><topic>Sliding mode control</topic><topic>Vibration</topic><topic>Vibration control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Phu, Do Xuan</creatorcontrib><creatorcontrib>Choi, Sang-Min</creatorcontrib><creatorcontrib>Choi, Seung-Bok</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Journal of vibration and control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Phu, Do Xuan</au><au>Choi, Sang-Min</au><au>Choi, Seung-Bok</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new adaptive hybrid controller for vibration control of a vehicle seat suspension featuring MR damper</atitle><jtitle>Journal of vibration and control</jtitle><date>2017-12-01</date><risdate>2017</risdate><volume>23</volume><issue>20</issue><spage>3392</spage><epage>3413</epage><pages>3392-3413</pages><issn>1077-5463</issn><eissn>1741-2986</eissn><abstract>This paper presents a new hybrid controller which is a combination of three control schemes: fuzzy neural control, PI control and sliding mode control. The interval type 2 fuzzy model featuring updated rules via online is used in this study and in order to support the fuzzy model, a granular clustering method is applied to find groups of data related to the initial fuzzy rule. Then the output for fuzzy model is used for the PI-sliding mode controller. The combination of PI and sliding mode controls is carried out by H-infinity technique method which is rely on the modified Riccati-like equation. After developing the mathematical model, the proposed controller is applied to vibration control of a vehicle seat suspension featuring magneto-rheological (MR) damper. In order to demonstrate the effectiveness of the proposed controller, two different excitations of bump and random signals are adopted and corresponding vibration control performances are evaluated. It is demonstrated through both simulation and experiment that the proposed controller can provide much better than vibration control performance compared with the conventional controllers showing more robust stability.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><doi>10.1177/1077546316629597</doi><tpages>22</tpages></addata></record> |
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| ispartof | Journal of vibration and control, 2017-12, Vol.23 (20), p.3392-3413 |
| issn | 1077-5463 1741-2986 |
| language | eng |
| recordid | cdi_proquest_journals_1980710111 |
| source | SAGE Complete A-Z List |
| subjects | Adaptive control Artificial neural networks Clustering Computer simulation Control stability Controllers Fuzzy control Fuzzy logic Neural networks Random signals Rheological properties Robust control Robustness (mathematics) Sliding mode control Vibration Vibration control |
| title | A new adaptive hybrid controller for vibration control of a vehicle seat suspension featuring MR damper |
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