Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design
Combining sliding mode control method with radial basis function neural network(RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle(NSHV) in the presence of parameter variations and external...
Gespeichert in:
| Veröffentlicht in: | IEEE/CAA journal of automatica sinica 2015-01, Vol.2 (1), p.94-101 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 101 |
|---|---|
| container_issue | 1 |
| container_start_page | 94 |
| container_title | IEEE/CAA journal of automatica sinica |
| container_volume | 2 |
| creator | Zhang, Jingmei Sun, Changyin Zhang, Ruimin Qian, Chengshan |
| description | Combining sliding mode control method with radial basis function neural network(RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle(NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances. |
| doi_str_mv | 10.1109/JAS.2015.7032910 |
| format | Article |
| fullrecord | <record><control><sourceid>wanfang_jour_RIE</sourceid><recordid>TN_cdi_wanfang_journals_zdhxb_ywb201501012</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><cqvip_id>90687266504849534849484950</cqvip_id><ieee_id>7032910</ieee_id><wanfj_id>zdhxb_ywb201501012</wanfj_id><sourcerecordid>zdhxb_ywb201501012</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2852-deaef876672f89b9e177e10c4e5cf23bd38cf75c677911b6bd1a39cf14b2275b3</originalsourceid><addsrcrecordid>eNpFkUtrGzEUhYfSQEKafSEbQXeFcfUYjUZL182jIUmhbrsVGs2VrdSVxtI4ifPrq4mNs5GOuN89gnOK4iPBE0Kw_HIznU8oJnwiMKOS4HfFCc2ilFRU7w-6ro-Ls5QeMMaEclHL6qRYTzvdD-4R0HzlOucX6C50gGbBDzGskA0R_YQS8muLpsPghk2eBovuQUc077UBdL3tIabgnUF_YOnMCtBXnaBDwWdh_qYB-n50_gbJLfyH4sjqVYKz_X1a_L68-DW7Lm9_XH2fTW9LQxtOyw402EbUtaC2ka0EIgQQbCrgxlLWdqwxVnBTCyEJaeu2I5pJY0nVUip4y06LzzvfJ-2t9gv1EDbR5x_VS7d8btX2qR0jwySHkeFPO7iPYb2BNLzRRHDJqoYLmSm8o0wMKUWwqo_un45bRbAai1C5CDW6qn0ReeV8t-IA4IC_TdnecBn8Yp1DOiAS143IlXFcNZXkbDxfFWb_AROakmk</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1759348579</pqid></control><display><type>article</type><title>Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design</title><source>IEEE Electronic Library (IEL)</source><creator>Zhang, Jingmei ; Sun, Changyin ; Zhang, Ruimin ; Qian, Chengshan</creator><creatorcontrib>Zhang, Jingmei ; Sun, Changyin ; Zhang, Ruimin ; Qian, Chengshan</creatorcontrib><description>Combining sliding mode control method with radial basis function neural network(RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle(NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances.</description><identifier>ISSN: 2329-9266</identifier><identifier>EISSN: 2329-9274</identifier><identifier>DOI: 10.1109/JAS.2015.7032910</identifier><identifier>CODEN: IJASJC</identifier><language>eng</language><publisher>Piscataway: Chinese Association of Automation (CAA)</publisher><subject>Attitude control ; Backstepping ; backstepping design ; Hypersonic vehicle ; Motors ; Neural networks ; Robustness ; Simulation ; Sliding mode control ; sliding mode control radial basis function neural network (RBFNN) ; Uncertainty ; Vehicles</subject><ispartof>IEEE/CAA journal of automatica sinica, 2015-01, Vol.2 (1), p.94-101</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2015</rights><rights>Copyright © Wanfang Data Co. Ltd. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2852-deaef876672f89b9e177e10c4e5cf23bd38cf75c677911b6bd1a39cf14b2275b3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://image.cqvip.com/vip1000/qk/61504X/61504X.jpg</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7032910$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7032910$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Zhang, Jingmei</creatorcontrib><creatorcontrib>Sun, Changyin</creatorcontrib><creatorcontrib>Zhang, Ruimin</creatorcontrib><creatorcontrib>Qian, Chengshan</creatorcontrib><title>Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design</title><title>IEEE/CAA journal of automatica sinica</title><addtitle>JAS</addtitle><addtitle>IEEE/CAA Journal of Automatica Sinica</addtitle><description>Combining sliding mode control method with radial basis function neural network(RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle(NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances.</description><subject>Attitude control</subject><subject>Backstepping</subject><subject>backstepping design</subject><subject>Hypersonic vehicle</subject><subject>Motors</subject><subject>Neural networks</subject><subject>Robustness</subject><subject>Simulation</subject><subject>Sliding mode control</subject><subject>sliding mode control radial basis function neural network (RBFNN)</subject><subject>Uncertainty</subject><subject>Vehicles</subject><issn>2329-9266</issn><issn>2329-9274</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpFkUtrGzEUhYfSQEKafSEbQXeFcfUYjUZL182jIUmhbrsVGs2VrdSVxtI4ifPrq4mNs5GOuN89gnOK4iPBE0Kw_HIznU8oJnwiMKOS4HfFCc2ilFRU7w-6ro-Ls5QeMMaEclHL6qRYTzvdD-4R0HzlOucX6C50gGbBDzGskA0R_YQS8muLpsPghk2eBovuQUc077UBdL3tIabgnUF_YOnMCtBXnaBDwWdh_qYB-n50_gbJLfyH4sjqVYKz_X1a_L68-DW7Lm9_XH2fTW9LQxtOyw402EbUtaC2ka0EIgQQbCrgxlLWdqwxVnBTCyEJaeu2I5pJY0nVUip4y06LzzvfJ-2t9gv1EDbR5x_VS7d8btX2qR0jwySHkeFPO7iPYb2BNLzRRHDJqoYLmSm8o0wMKUWwqo_un45bRbAai1C5CDW6qn0ReeV8t-IA4IC_TdnecBn8Yp1DOiAS143IlXFcNZXkbDxfFWb_AROakmk</recordid><startdate>20150110</startdate><enddate>20150110</enddate><creator>Zhang, Jingmei</creator><creator>Sun, Changyin</creator><creator>Zhang, Ruimin</creator><creator>Qian, Chengshan</creator><general>Chinese Association of Automation (CAA)</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><general>Flight Control Research Center, Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, School of Automation, Southeast University, Nanjing 210096, China%College of Information and Control, Nanjing University of Information Science&Technology,Nanjing 210044,China</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>~WA</scope><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><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>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>20150110</creationdate><title>Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design</title><author>Zhang, Jingmei ; Sun, Changyin ; Zhang, Ruimin ; Qian, Chengshan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2852-deaef876672f89b9e177e10c4e5cf23bd38cf75c677911b6bd1a39cf14b2275b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Attitude control</topic><topic>Backstepping</topic><topic>backstepping design</topic><topic>Hypersonic vehicle</topic><topic>Motors</topic><topic>Neural networks</topic><topic>Robustness</topic><topic>Simulation</topic><topic>Sliding mode control</topic><topic>sliding mode control radial basis function neural network (RBFNN)</topic><topic>Uncertainty</topic><topic>Vehicles</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Jingmei</creatorcontrib><creatorcontrib>Sun, Changyin</creatorcontrib><creatorcontrib>Zhang, Ruimin</creatorcontrib><creatorcontrib>Qian, Chengshan</creatorcontrib><collection>中文科技期刊数据库</collection><collection>中文科技期刊数据库-CALIS站点</collection><collection>中文科技期刊数据库-7.0平台</collection><collection>中文科技期刊数据库- 镜像站点</collection><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><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>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts 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>IEEE/CAA journal of automatica sinica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zhang, Jingmei</au><au>Sun, Changyin</au><au>Zhang, Ruimin</au><au>Qian, Chengshan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design</atitle><jtitle>IEEE/CAA journal of automatica sinica</jtitle><stitle>JAS</stitle><addtitle>IEEE/CAA Journal of Automatica Sinica</addtitle><date>2015-01-10</date><risdate>2015</risdate><volume>2</volume><issue>1</issue><spage>94</spage><epage>101</epage><pages>94-101</pages><issn>2329-9266</issn><eissn>2329-9274</eissn><coden>IJASJC</coden><abstract>Combining sliding mode control method with radial basis function neural network(RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle(NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances.</abstract><cop>Piscataway</cop><pub>Chinese Association of Automation (CAA)</pub><doi>10.1109/JAS.2015.7032910</doi><tpages>8</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 2329-9266 |
| ispartof | IEEE/CAA journal of automatica sinica, 2015-01, Vol.2 (1), p.94-101 |
| issn | 2329-9266 2329-9274 |
| language | eng |
| recordid | cdi_wanfang_journals_zdhxb_ywb201501012 |
| source | IEEE Electronic Library (IEL) |
| subjects | Attitude control Backstepping backstepping design Hypersonic vehicle Motors Neural networks Robustness Simulation Sliding mode control sliding mode control radial basis function neural network (RBFNN) Uncertainty Vehicles |
| title | Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-09T11%3A01%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-wanfang_jour_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Adaptive%20Sliding%20Mode%20Control%20for%20Re-entry%20Attitude%20of%20Near%20Space%20Hypersonic%20Vehicle%20Based%20on%20Backstepping%20Design&rft.jtitle=IEEE/CAA%20journal%20of%20automatica%20sinica&rft.au=Zhang,%20Jingmei&rft.date=2015-01-10&rft.volume=2&rft.issue=1&rft.spage=94&rft.epage=101&rft.pages=94-101&rft.issn=2329-9266&rft.eissn=2329-9274&rft.coden=IJASJC&rft_id=info:doi/10.1109/JAS.2015.7032910&rft_dat=%3Cwanfang_jour_RIE%3Ezdhxb_ywb201501012%3C/wanfang_jour_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1759348579&rft_id=info:pmid/&rft_cqvip_id=90687266504849534849484950&rft_ieee_id=7032910&rft_wanfj_id=zdhxb_ywb201501012&rfr_iscdi=true |