Identification and nonlinear model predictive control of MIMO Hammerstein system with constraints
This work is concerned with identification and nonlinear predictive control method for M1MO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method is introduced to MIMO Hammerstein system. A modified version of artificial bee colo...
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| Veröffentlicht in: | Journal of Central South University 2017-02, Vol.24 (2), p.448-458 |
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| container_title | Journal of Central South University |
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| creator | 李大字 贾元昕 李全善 靳其兵 |
| description | This work is concerned with identification and nonlinear predictive control method for M1MO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method is introduced to MIMO Hammerstein system. A modified version of artificial bee colony algorithm is proposed to improve the prediction ability of Hammerstein model. Next, a computationally efficient nonlinear model predictive control algorithm （MGPC） is developed to deal with constrained problem of MIMO system. The identification process and performance of MGPC are shown. Numerical results about a polymerization reactor validate the effectiveness of the proposed method and the comparisons show that MGPC has a better performance than QDMC and basic GPC. |
| doi_str_mv | 10.1007/s11771-017-3447-3 |
| format | Article |
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Cent. South Univ</addtitle><addtitle>Journal of Central South University of Technology</addtitle><description>This work is concerned with identification and nonlinear predictive control method for M1MO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method is introduced to MIMO Hammerstein system. A modified version of artificial bee colony algorithm is proposed to improve the prediction ability of Hammerstein model. Next, a computationally efficient nonlinear model predictive control algorithm （MGPC） is developed to deal with constrained problem of MIMO system. The identification process and performance of MGPC are shown. Numerical results about a polymerization reactor validate the effectiveness of the proposed method and the comparisons show that MGPC has a better performance than QDMC and basic GPC.</description><subject>Engineering</subject><subject>Metallic Materials</subject><subject>Nonlinear control</subject><subject>Predictive control</subject><issn>2095-2899</issn><issn>2227-5223</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LAzEQhhdRsGh_gLeg59VMkv3IUYraQksveg7ZbLaN7CZtkir996ZsEU8yMDOH9wOeLLsD_AgYV08BoKogx1DllLG0LrIJIaTKC0LoZfoxL3JSc36dTUMwDaZASlrycpLJRattNJ1RMhpnkbQtss72xmrp0eBa3aOd161R0XxppJyN3vXIdWi1WK3RXA6D9iFqY1E4pjugbxO3J12IXhobw2121ck-6On53mQfry_vs3m-XL8tZs_LXFFGYw4NbVpG6q7UhUrDVMkwwZiqVmqmuWJd2XQFx5wDx6wA2WDFVE0rVUsMhN5kD2Puzrv9QYcoPt3B21QpoOYUqoJCkVQwqpR3IXjdiZ03g_RHAVicYIoRpkgwxQmmoMlDRk9IWrvR_k_yP6b7c9HW2c0--X6byooAIbik9AcRr4Mr</recordid><startdate>20170201</startdate><enddate>20170201</enddate><creator>李大字 贾元昕 李全善 靳其兵</creator><general>Central South University</general><general>Springer Nature B.V</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>W92</scope><scope>~WA</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20170201</creationdate><title>Identification and nonlinear model predictive control of MIMO Hammerstein system with constraints</title><author>李大字 贾元昕 李全善 靳其兵</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c343t-1b3bd428f6e5c5c54c6402003cdae4e9c4f6bf59099190451ab0c4c837c8a0123</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Engineering</topic><topic>Metallic Materials</topic><topic>Nonlinear control</topic><topic>Predictive control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>李大字 贾元昕 李全善 靳其兵</creatorcontrib><collection>维普_期刊</collection><collection>中文科技期刊数据库-CALIS站点</collection><collection>维普中文期刊数据库</collection><collection>中文科技期刊数据库-工程技术</collection><collection>中文科技期刊数据库- 镜像站点</collection><collection>CrossRef</collection><jtitle>Journal of Central South University</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>李大字 贾元昕 李全善 靳其兵</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification and nonlinear model predictive control of MIMO Hammerstein system with constraints</atitle><jtitle>Journal of Central South University</jtitle><stitle>J. Cent. South Univ</stitle><addtitle>Journal of Central South University of Technology</addtitle><date>2017-02-01</date><risdate>2017</risdate><volume>24</volume><issue>2</issue><spage>448</spage><epage>458</epage><pages>448-458</pages><issn>2095-2899</issn><eissn>2227-5223</eissn><abstract>This work is concerned with identification and nonlinear predictive control method for M1MO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method is introduced to MIMO Hammerstein system. A modified version of artificial bee colony algorithm is proposed to improve the prediction ability of Hammerstein model. Next, a computationally efficient nonlinear model predictive control algorithm （MGPC） is developed to deal with constrained problem of MIMO system. The identification process and performance of MGPC are shown. 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| ispartof | Journal of Central South University, 2017-02, Vol.24 (2), p.448-458 |
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| subjects | Engineering Metallic Materials Nonlinear control Predictive control |
| title | Identification and nonlinear model predictive control of MIMO Hammerstein system with constraints |
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