ADP-based Optimal Control for Systems with Mismatched Disturbances: A PMSM Application
In this brief, in order to optimize the tracking accuracy and enhance the robustness of the tracking process for permanent magnet synchronous motor (PMSM), an adaptive dynamic programming(ADP)-based optimal control strategy combining with anti-disturbance control method is proposed. We consider the...
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| Veröffentlicht in: | IEEE transactions on circuits and systems. II, Express briefs Express briefs, 2023-06, Vol.70 (6), p.1-1 |
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| container_title | IEEE transactions on circuits and systems. II, Express briefs |
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| creator | Fan, Zhong-Xin Li, Shihua Liu, Rongjie |
| description | In this brief, in order to optimize the tracking accuracy and enhance the robustness of the tracking process for permanent magnet synchronous motor (PMSM), an adaptive dynamic programming(ADP)-based optimal control strategy combining with anti-disturbance control method is proposed. We consider the unknown, mismatched and time-varying load torque as a disturbance and a disturbance observer is then designed. Based on the output of the disturbance observer, a feedforward control can compensate the disturbance in the PMSM in real time. For the easy implementation of optimal control, this brief adopts the actor-critic neural network to approximate the value function and the optimal controller, respectively. A composite controller is then proposed to ensure that the speed can track the reference signal in an optimal and robust way. Finally, an experiment based on a motor towed platform is given to prove the optimality and robustness. |
| doi_str_mv | 10.1109/TCSII.2022.3233356 |
| format | Article |
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We consider the unknown, mismatched and time-varying load torque as a disturbance and a disturbance observer is then designed. Based on the output of the disturbance observer, a feedforward control can compensate the disturbance in the PMSM in real time. For the easy implementation of optimal control, this brief adopts the actor-critic neural network to approximate the value function and the optimal controller, respectively. A composite controller is then proposed to ensure that the speed can track the reference signal in an optimal and robust way. 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(IEEE) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c296t-3b65c036a665ac36073804f09168b1832f10ef93334472c3278bfb374c1528b73</citedby><cites>FETCH-LOGICAL-c296t-3b65c036a665ac36073804f09168b1832f10ef93334472c3278bfb374c1528b73</cites><orcidid>0000-0001-9044-7137 ; 0000-0003-1653-8609 ; 0000-0002-9408-7236</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10004719$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>315,781,785,797,27929,27930,54763</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10004719$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Fan, Zhong-Xin</creatorcontrib><creatorcontrib>Li, Shihua</creatorcontrib><creatorcontrib>Liu, Rongjie</creatorcontrib><title>ADP-based Optimal Control for Systems with Mismatched Disturbances: A PMSM Application</title><title>IEEE transactions on circuits and systems. II, Express briefs</title><addtitle>TCSII</addtitle><description>In this brief, in order to optimize the tracking accuracy and enhance the robustness of the tracking process for permanent magnet synchronous motor (PMSM), an adaptive dynamic programming(ADP)-based optimal control strategy combining with anti-disturbance control method is proposed. We consider the unknown, mismatched and time-varying load torque as a disturbance and a disturbance observer is then designed. Based on the output of the disturbance observer, a feedforward control can compensate the disturbance in the PMSM in real time. For the easy implementation of optimal control, this brief adopts the actor-critic neural network to approximate the value function and the optimal controller, respectively. A composite controller is then proposed to ensure that the speed can track the reference signal in an optimal and robust way. Finally, an experiment based on a motor towed platform is given to prove the optimality and robustness.</description><subject>actor-critic neural network</subject><subject>Adaptive control</subject><subject>Adaptive dynamic programming</subject><subject>Biological neural networks</subject><subject>Control methods</subject><subject>Controllers</subject><subject>disturbance observer</subject><subject>Disturbance observers</subject><subject>Dynamic programming</subject><subject>Feedforward control</subject><subject>Neural networks</subject><subject>Optimal control</subject><subject>Optimization</subject><subject>Permanent magnet motors</subject><subject>Permanent magnets</subject><subject>PMSM</subject><subject>Reference signals</subject><subject>Robustness</subject><subject>Synchronous motors</subject><subject>Torque</subject><subject>Tracking</subject><issn>1549-7747</issn><issn>1558-3791</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkMtOwzAQRS0EEqXwA4iFJdYpYzuxY3ZRyqNSq1ZqYWs5xlFTpUmwHaH-PSntgtXM4p4Z3YPQPYEJISCfNvl6NptQoHTCKGMs4RdoRJIkjZiQ5PK4xzISIhbX6Mb7HQCVwOgIfWbTVVRob7_wsgvVXtc4b5vg2hqXrcPrgw927_FPFbZ4Ufm9DmY7ZKeVD70rdGOsf8YZXi3WC5x1XV0ZHaq2uUVXpa69vTvPMfp4fdnk79F8-TbLs3lkqOQhYgVPDDCuOU-0YRwESyEuQRKeFiRltCRgSzkUimNBDaMiLcqCidiQhKaFYGP0eLrbufa7tz6oXdu7ZnipaEoJiIRzGFL0lDKu9d7ZUnVuqOoOioA6-lN__tTRnzr7G6CHE1RZa_8BALEgkv0CYD5p1Q</recordid><startdate>20230601</startdate><enddate>20230601</enddate><creator>Fan, Zhong-Xin</creator><creator>Li, Shihua</creator><creator>Liu, Rongjie</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| ispartof | IEEE transactions on circuits and systems. II, Express briefs, 2023-06, Vol.70 (6), p.1-1 |
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| source | IEEE Electronic Library (IEL) |
| subjects | actor-critic neural network Adaptive control Adaptive dynamic programming Biological neural networks Control methods Controllers disturbance observer Disturbance observers Dynamic programming Feedforward control Neural networks Optimal control Optimization Permanent magnet motors Permanent magnets PMSM Reference signals Robustness Synchronous motors Torque Tracking |
| title | ADP-based Optimal Control for Systems with Mismatched Disturbances: A PMSM Application |
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