Trajectory Tracking of a Piezoelectric System using State Compensated Iterative Learning Control
This paper proposes a novel scheme of state compensated iterative learning control (ILC) for trajectory tracking of piezoelectric systems. The new ILC scheme adds a state compensation term to the conventional Arimoto-type ILC formula. The state compensation term is based on the difference of trackin...
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creator | Chiang-Ju Chien Fu-Shin Lee Jhen-Cheng Wang |
description | This paper proposes a novel scheme of state compensated iterative learning control (ILC) for trajectory tracking of piezoelectric systems. The new ILC scheme adds a state compensation term to the conventional Arimoto-type ILC formula. The state compensation term is based on the difference of tracking error between the current and previous iterations. With the aid of this state compensation, iterative learning control can therefore take effect more precisely as desired. Further, the addition of the current error in the compensation term can also serve the role of feedback control to stabilize the system. The new ILC scheme keeps the simplicity feature of conventional iterative learning control that no model is required for control purpose. Experimental results demonstrate that a piezoelectric actuator using the proposed learning scheme can achieve error convergence in about three to five iterations, and keep steady-state tracking errors reaching the system noise level. |
doi_str_mv | 10.1109/CDC.2005.1583092 |
format | Conference Proceeding |
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The new ILC scheme adds a state compensation term to the conventional Arimoto-type ILC formula. The state compensation term is based on the difference of tracking error between the current and previous iterations. With the aid of this state compensation, iterative learning control can therefore take effect more precisely as desired. Further, the addition of the current error in the compensation term can also serve the role of feedback control to stabilize the system. The new ILC scheme keeps the simplicity feature of conventional iterative learning control that no model is required for control purpose. Experimental results demonstrate that a piezoelectric actuator using the proposed learning scheme can achieve error convergence in about three to five iterations, and keep steady-state tracking errors reaching the system noise level.</description><identifier>ISSN: 0191-2216</identifier><identifier>ISBN: 9780780395671</identifier><identifier>ISBN: 0780395670</identifier><identifier>DOI: 10.1109/CDC.2005.1583092</identifier><language>eng</language><publisher>IEEE</publisher><subject>Control systems ; Crystalline materials ; Error correction ; Ferroelectric materials ; Hysteresis ; Optical materials ; Piezoelectric actuators ; Piezoelectric polarization ; Sliding mode control ; Trajectory</subject><ispartof>Proceedings of the 44th IEEE Conference on Decision and Control, 2005, p.5826-5831</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1583092$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1583092$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Chiang-Ju Chien</creatorcontrib><creatorcontrib>Fu-Shin Lee</creatorcontrib><creatorcontrib>Jhen-Cheng Wang</creatorcontrib><title>Trajectory Tracking of a Piezoelectric System using State Compensated Iterative Learning Control</title><title>Proceedings of the 44th IEEE Conference on Decision and Control</title><addtitle>CDC</addtitle><description>This paper proposes a novel scheme of state compensated iterative learning control (ILC) for trajectory tracking of piezoelectric systems. The new ILC scheme adds a state compensation term to the conventional Arimoto-type ILC formula. The state compensation term is based on the difference of tracking error between the current and previous iterations. With the aid of this state compensation, iterative learning control can therefore take effect more precisely as desired. Further, the addition of the current error in the compensation term can also serve the role of feedback control to stabilize the system. The new ILC scheme keeps the simplicity feature of conventional iterative learning control that no model is required for control purpose. Experimental results demonstrate that a piezoelectric actuator using the proposed learning scheme can achieve error convergence in about three to five iterations, and keep steady-state tracking errors reaching the system noise level.</description><subject>Control systems</subject><subject>Crystalline materials</subject><subject>Error correction</subject><subject>Ferroelectric materials</subject><subject>Hysteresis</subject><subject>Optical materials</subject><subject>Piezoelectric actuators</subject><subject>Piezoelectric polarization</subject><subject>Sliding mode control</subject><subject>Trajectory</subject><issn>0191-2216</issn><isbn>9780780395671</isbn><isbn>0780395670</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2005</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotkFtLxDAUhAMquK77LviSP9B6TtskzaPU20JBYdfnNW1PJGsvSxqF-uvt4sLADHzDPAxjNwgxIui74qGIEwARo8hT0MkZW2mVw6xUC6nwnC0ANUZJgvKSXY3jHgBykHLBPrbe7KkOg5_4HOsv13_ywXLD3xz9DtTOzLuab6YxUMe_xyPfBBOIF0N3oH6cY8PXgbwJ7od4Scb3x1Ix9MEP7TW7sKYdaXXyJXt_etwWL1H5-rwu7svIoRIhQhKNSFUlNWCqMhKZltIkWNcSBDWNrZTQlWqkVVmFUlSZRUvGNlZZJVSVLtnt_64jot3Bu874aXc6JP0DSJVVxA</recordid><startdate>2005</startdate><enddate>2005</enddate><creator>Chiang-Ju Chien</creator><creator>Fu-Shin Lee</creator><creator>Jhen-Cheng Wang</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>2005</creationdate><title>Trajectory Tracking of a Piezoelectric System using State Compensated Iterative Learning Control</title><author>Chiang-Ju Chien ; Fu-Shin Lee ; Jhen-Cheng Wang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-1e5d537b6901374e54966a21cc605eddfb759b7d6f74b165b4f1feafdf7f757b3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Control systems</topic><topic>Crystalline materials</topic><topic>Error correction</topic><topic>Ferroelectric materials</topic><topic>Hysteresis</topic><topic>Optical materials</topic><topic>Piezoelectric actuators</topic><topic>Piezoelectric polarization</topic><topic>Sliding mode control</topic><topic>Trajectory</topic><toplevel>online_resources</toplevel><creatorcontrib>Chiang-Ju Chien</creatorcontrib><creatorcontrib>Fu-Shin Lee</creatorcontrib><creatorcontrib>Jhen-Cheng Wang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Chiang-Ju Chien</au><au>Fu-Shin Lee</au><au>Jhen-Cheng Wang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Trajectory Tracking of a Piezoelectric System using State Compensated Iterative Learning Control</atitle><btitle>Proceedings of the 44th IEEE Conference on Decision and Control</btitle><stitle>CDC</stitle><date>2005</date><risdate>2005</risdate><spage>5826</spage><epage>5831</epage><pages>5826-5831</pages><issn>0191-2216</issn><isbn>9780780395671</isbn><isbn>0780395670</isbn><abstract>This paper proposes a novel scheme of state compensated iterative learning control (ILC) for trajectory tracking of piezoelectric systems. The new ILC scheme adds a state compensation term to the conventional Arimoto-type ILC formula. The state compensation term is based on the difference of tracking error between the current and previous iterations. With the aid of this state compensation, iterative learning control can therefore take effect more precisely as desired. Further, the addition of the current error in the compensation term can also serve the role of feedback control to stabilize the system. The new ILC scheme keeps the simplicity feature of conventional iterative learning control that no model is required for control purpose. Experimental results demonstrate that a piezoelectric actuator using the proposed learning scheme can achieve error convergence in about three to five iterations, and keep steady-state tracking errors reaching the system noise level.</abstract><pub>IEEE</pub><doi>10.1109/CDC.2005.1583092</doi><tpages>6</tpages></addata></record> |
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subjects | Control systems Crystalline materials Error correction Ferroelectric materials Hysteresis Optical materials Piezoelectric actuators Piezoelectric polarization Sliding mode control Trajectory |
title | Trajectory Tracking of a Piezoelectric System using State Compensated Iterative Learning Control |
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