An Adaptive Single Neural Control for Variable Step-Size P&O MPPT of Marine Current Turbine System
Marine current energy has been increasingly used because of its predictable higher power potential. Owing to the external disturbances of various flow velocity and the high nonlinear effects on the marine current turbine (MCT) system, the nonlinear controllers which rely on precise mathematical mode...
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| Veröffentlicht in: | China ocean engineering 2021-09, Vol.35 (5), p.750-758 |
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| creator | Li, Ming-zhu Wang, Tian-zhen Zhou, Fu-na Shi, Ming |
| description | Marine current energy has been increasingly used because of its predictable higher power potential. Owing to the external disturbances of various flow velocity and the high nonlinear effects on the marine current turbine (MCT) system, the nonlinear controllers which rely on precise mathematical models show poor performance under a high level of parameters’ uncertainties. This paper proposes an adaptive single neural control (ASNC) strategy for variable step-size perturb and observe (P&O) maximum power point tracking (MPPT) control. Firstly, to automatically update the neuron weights of SNC for the nonlinear systems, an adaptive mechanism is proposed to adaptively adjust the weighting and learning coefficients. Secondly, aiming to generate the exact reference speed for ASNC to extract the maximum power, a variable step-size law based on speed increment is designed to strike a balance between tracking speed and accuracy of P&O MPPT. The robust stability of the MCT control system is guaranteed by the Lyapunov theorem. Comparative simulation results show that this strategy has favorable adaptive performance under variable velocity conditions, and the MCT system operates at maximum power point steadily. |
| doi_str_mv | 10.1007/s13344-021-0066-4 |
| format | Article |
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Owing to the external disturbances of various flow velocity and the high nonlinear effects on the marine current turbine (MCT) system, the nonlinear controllers which rely on precise mathematical models show poor performance under a high level of parameters’ uncertainties. This paper proposes an adaptive single neural control (ASNC) strategy for variable step-size perturb and observe (P&O) maximum power point tracking (MPPT) control. Firstly, to automatically update the neuron weights of SNC for the nonlinear systems, an adaptive mechanism is proposed to adaptively adjust the weighting and learning coefficients. Secondly, aiming to generate the exact reference speed for ASNC to extract the maximum power, a variable step-size law based on speed increment is designed to strike a balance between tracking speed and accuracy of P&O MPPT. The robust stability of the MCT control system is guaranteed by the Lyapunov theorem. Comparative simulation results show that this strategy has favorable adaptive performance under variable velocity conditions, and the MCT system operates at maximum power point steadily.</description><identifier>ISSN: 0890-5487</identifier><identifier>EISSN: 2191-8945</identifier><identifier>DOI: 10.1007/s13344-021-0066-4</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Adaptive control ; Adaptive systems ; Coastal Sciences ; Coefficients ; Control ; Control stability ; Control systems ; Engineering ; Flow velocity ; Fluid- and Aerodynamics ; Marine & Freshwater Sciences ; Mathematical models ; Maximum power tracking ; Nonlinear control ; Nonlinear systems ; Numerical and Computational Physics ; Oceanography ; Offshore Engineering ; Parameter uncertainty ; Robustness (mathematics) ; Simulation ; Tracking control ; Turbine engines ; Turbines ; Velocity</subject><ispartof>China ocean engineering, 2021-09, Vol.35 (5), p.750-758</ispartof><rights>Chinese Ocean Engineering Society and Springer-Verlag GmbH Germany, part of Springer Nature 2021</rights><rights>Chinese Ocean Engineering Society and Springer-Verlag GmbH Germany, part of Springer Nature 2021.</rights><rights>Copyright © Wanfang Data Co. 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All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c393t-ecee7fddd19390412d59c59a9c6be4bce2c5c6761285ffbd13cae598d50859ad3</citedby><cites>FETCH-LOGICAL-c393t-ecee7fddd19390412d59c59a9c6be4bce2c5c6761285ffbd13cae598d50859ad3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://www.wanfangdata.com.cn/images/PeriodicalImages/zghygc-e/zghygc-e.jpg</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s13344-021-0066-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s13344-021-0066-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,777,781,27905,27906,41469,42538,51300</link.rule.ids></links><search><creatorcontrib>Li, Ming-zhu</creatorcontrib><creatorcontrib>Wang, Tian-zhen</creatorcontrib><creatorcontrib>Zhou, Fu-na</creatorcontrib><creatorcontrib>Shi, Ming</creatorcontrib><title>An Adaptive Single Neural Control for Variable Step-Size P&O MPPT of Marine Current Turbine System</title><title>China ocean engineering</title><addtitle>China Ocean Eng</addtitle><description>Marine current energy has been increasingly used because of its predictable higher power potential. Owing to the external disturbances of various flow velocity and the high nonlinear effects on the marine current turbine (MCT) system, the nonlinear controllers which rely on precise mathematical models show poor performance under a high level of parameters’ uncertainties. This paper proposes an adaptive single neural control (ASNC) strategy for variable step-size perturb and observe (P&O) maximum power point tracking (MPPT) control. Firstly, to automatically update the neuron weights of SNC for the nonlinear systems, an adaptive mechanism is proposed to adaptively adjust the weighting and learning coefficients. Secondly, aiming to generate the exact reference speed for ASNC to extract the maximum power, a variable step-size law based on speed increment is designed to strike a balance between tracking speed and accuracy of P&O MPPT. The robust stability of the MCT control system is guaranteed by the Lyapunov theorem. Comparative simulation results show that this strategy has favorable adaptive performance under variable velocity conditions, and the MCT system operates at maximum power point steadily.</description><subject>Adaptive control</subject><subject>Adaptive systems</subject><subject>Coastal Sciences</subject><subject>Coefficients</subject><subject>Control</subject><subject>Control stability</subject><subject>Control systems</subject><subject>Engineering</subject><subject>Flow velocity</subject><subject>Fluid- and Aerodynamics</subject><subject>Marine & Freshwater Sciences</subject><subject>Mathematical models</subject><subject>Maximum power tracking</subject><subject>Nonlinear control</subject><subject>Nonlinear systems</subject><subject>Numerical and Computational Physics</subject><subject>Oceanography</subject><subject>Offshore Engineering</subject><subject>Parameter uncertainty</subject><subject>Robustness (mathematics)</subject><subject>Simulation</subject><subject>Tracking control</subject><subject>Turbine engines</subject><subject>Turbines</subject><subject>Velocity</subject><issn>0890-5487</issn><issn>2191-8945</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp1kNFq2zAUhkVZoVnbB-idoDDYhbYjWbKtyxC2dpCugaS9FbJ87LokcibZG8nTT8GDXO3qcDjf_x_4CLnj8IUDFF8jzzIpGQjOAPKcyQsyE1xzVmqpPpAZlBqYkmVxRT7G-A6guJJ8Rqq5p_Pa7ofuN9J159st0p84Bruli94Pod_Spg_01YbOVum2HnDP1t0R6erTM31arTa0b-hTOnukizEE9APdjKE67etDHHB3Qy4bu414-29ek5fv3zaLR7Z8fvixmC-Zy3Q2MHSIRVPXNdeZBslFrbRT2mqXVygrh8Iplxc5F6VqmqrmmbOodFkrKBNWZ9fk89T7x_rG-ta892Pw6aM5tm-H1hkUSQ8o4JDY-4ndh_7XiHE4w0JpnfNCgEwUnygX-hgDNmYfup0NB8PBnLSbSbtJveak3ZwyYsrExPoWw7n5_6G_BMeEDg</recordid><startdate>20210901</startdate><enddate>20210901</enddate><creator>Li, Ming-zhu</creator><creator>Wang, Tian-zhen</creator><creator>Zhou, Fu-na</creator><creator>Shi, Ming</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><general>Logistics Engineering College,Shanghai Maritime University,Shanghai 201306,China%Shanghai Investigation,Design and Research Institute Co.,Ltd,Shanghai 200434,China</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TN</scope><scope>F1W</scope><scope>H96</scope><scope>L.G</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>20210901</creationdate><title>An Adaptive Single Neural Control for Variable Step-Size P&O MPPT of Marine Current Turbine System</title><author>Li, Ming-zhu ; Wang, Tian-zhen ; Zhou, Fu-na ; Shi, Ming</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c393t-ecee7fddd19390412d59c59a9c6be4bce2c5c6761285ffbd13cae598d50859ad3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adaptive control</topic><topic>Adaptive systems</topic><topic>Coastal Sciences</topic><topic>Coefficients</topic><topic>Control</topic><topic>Control stability</topic><topic>Control systems</topic><topic>Engineering</topic><topic>Flow velocity</topic><topic>Fluid- and Aerodynamics</topic><topic>Marine & Freshwater Sciences</topic><topic>Mathematical models</topic><topic>Maximum power tracking</topic><topic>Nonlinear control</topic><topic>Nonlinear systems</topic><topic>Numerical and Computational Physics</topic><topic>Oceanography</topic><topic>Offshore Engineering</topic><topic>Parameter uncertainty</topic><topic>Robustness (mathematics)</topic><topic>Simulation</topic><topic>Tracking control</topic><topic>Turbine engines</topic><topic>Turbines</topic><topic>Velocity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Ming-zhu</creatorcontrib><creatorcontrib>Wang, Tian-zhen</creatorcontrib><creatorcontrib>Zhou, Fu-na</creatorcontrib><creatorcontrib>Shi, Ming</creatorcontrib><collection>CrossRef</collection><collection>Oceanic Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>China ocean engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Ming-zhu</au><au>Wang, Tian-zhen</au><au>Zhou, Fu-na</au><au>Shi, Ming</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Adaptive Single Neural Control for Variable Step-Size P&O MPPT of Marine Current Turbine System</atitle><jtitle>China ocean engineering</jtitle><stitle>China Ocean Eng</stitle><date>2021-09-01</date><risdate>2021</risdate><volume>35</volume><issue>5</issue><spage>750</spage><epage>758</epage><pages>750-758</pages><issn>0890-5487</issn><eissn>2191-8945</eissn><abstract>Marine current energy has been increasingly used because of its predictable higher power potential. Owing to the external disturbances of various flow velocity and the high nonlinear effects on the marine current turbine (MCT) system, the nonlinear controllers which rely on precise mathematical models show poor performance under a high level of parameters’ uncertainties. This paper proposes an adaptive single neural control (ASNC) strategy for variable step-size perturb and observe (P&O) maximum power point tracking (MPPT) control. Firstly, to automatically update the neuron weights of SNC for the nonlinear systems, an adaptive mechanism is proposed to adaptively adjust the weighting and learning coefficients. Secondly, aiming to generate the exact reference speed for ASNC to extract the maximum power, a variable step-size law based on speed increment is designed to strike a balance between tracking speed and accuracy of P&O MPPT. The robust stability of the MCT control system is guaranteed by the Lyapunov theorem. Comparative simulation results show that this strategy has favorable adaptive performance under variable velocity conditions, and the MCT system operates at maximum power point steadily.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s13344-021-0066-4</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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| source | Springer Nature - Complete Springer Journals; Alma/SFX Local Collection |
| subjects | Adaptive control Adaptive systems Coastal Sciences Coefficients Control Control stability Control systems Engineering Flow velocity Fluid- and Aerodynamics Marine & Freshwater Sciences Mathematical models Maximum power tracking Nonlinear control Nonlinear systems Numerical and Computational Physics Oceanography Offshore Engineering Parameter uncertainty Robustness (mathematics) Simulation Tracking control Turbine engines Turbines Velocity |
| title | An Adaptive Single Neural Control for Variable Step-Size P&O MPPT of Marine Current Turbine System |
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