A RBF neural network sliding mode controller for SMA actuator
A radial basis function neural network sliding-mode controller (RBFSMC) is proposed to control a shape memory alloy (SMA) actuator. This approach, which combines a RBF neural network with sliding-mode control (SMC), is presented for the tracking control of a class of nonlinear systems having paramet...
Saved in:
| Published in: | International journal of control, automation, and systems Vol. 8; no. 6; pp. 1296 - 1305 |
|---|---|
| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Heidelberg
Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers
01-12-2010
Springer Nature B.V 제어·로봇·시스템학회 |
| Subjects: | |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | A radial basis function neural network sliding-mode controller (RBFSMC) is proposed to control a shape memory alloy (SMA) actuator. This approach, which combines a RBF neural network with sliding-mode control (SMC), is presented for the tracking control of a class of nonlinear systems having parameter uncertainties. The centers and output weights of the RBF neural network are updated through on-line learning, which causes the output of the neural network control to approximate the sliding-mode equivalent control along the direction that makes the sliding-mode asymptotically stable. Using Lyapunov theory, the asymptotic stability of the overall system is proven. Then, the controller is applied to compensate for the hysteresis phenomenon seen in SMA. The results show that the controller was applied successfully. The control results are also compared to those of a conventional SMC. |
|---|---|
| AbstractList | A radial basis function neural network sliding-mode controller (RBFSMC) is proposed to control a shape memory alloy (SMA) actuator. This approach, which combines a RBF neural network with sliding-mode control (SMC), is presented for the tracking control of a class of nonlinear systems having parameter uncertainties. The centers and output weights of the RBF neural network are updated through on-line learning, which causes the output of the neural network control to approximate the sliding-mode equivalent control along the direction that makes the sliding-mode asymptotically stable. Using Lyapunov theory, the asymptotic stability of the overall system is proven. Then, the controller is applied to compensate for the hysteresis phenomenon seen in SMA. The results show that the controller was applied successfully. The control results are also compared to those of a conventional SMC. A radial basis function neural network sliding-mode controller (RBFSMC) is proposed to control a shape memory alloy (SMA) actuator. This approach, which combines a RBF neural network with slid-ing-mode control (SMC), is presented for the tracking control of a class of nonlinear systems having parameter uncertainties. The centers and output weights of the RBF neural network are updated through on-line learning, which causes the output of the neural network control to approximate the sliding-mode equivalent control along the direction that makes the sliding-mode asymptotically stable. Using Lyapunov theory, the asymptotic stability of the overall system is proven. Then, the controller is applied to compensate for the hysteresis phenomenon seen in SMA. The results show that the control-ler was applied successfully. The control results are also compared to those of a conventional SMC. KCI Citation Count: 26 A radial basis function neural network sliding-mode controller (RBFSMC) is proposed to control a shape memory alloy (SMA) actuator. This approach, which combines a RBF neural network with sliding-mode control (SMC), is presented for the tracking control of a class of nonlinear systems having parameter uncertainties. The centers and output weights of the RBF neural network are updated through on-line learning, which causes the output of the neural network control to approximate the sliding-mode equivalent control along the direction that makes the sliding-mode asymptotically stable. Using Lyapunov theory, the asymptotic stability of the overall system is proven. Then, the controller is applied to compensate for the hysteresis phenomenon seen in SMA. The results show that the controller was applied successfully. The control results are also compared to those of a conventional SMC.[PUBLICATION ABSTRACT] |
| Author | Tai, Nguyen Trong Ahn, Kyoung Kwan |
| Author_xml | – sequence: 1 givenname: Nguyen Trong surname: Tai fullname: Tai, Nguyen Trong organization: School of Mechanical and Automative Engineering, University of Ulsan – sequence: 2 givenname: Kyoung Kwan surname: Ahn fullname: Ahn, Kyoung Kwan email: kkahn@ulsan.ac.kr organization: School of Mechanical and Automative Engineering, University of Ulsan |
| BackLink | https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART001497811$$DAccess content in National Research Foundation of Korea (NRF) |
| BookMark | eNp1kEFLwzAYhoMouE1_gLfiyUs1X9I06cFDHU4HE2HOc0jTdHTrkpm0iP_ezgoDwdMLH8_7wveM0al11iB0BfgWMOZ3AQhjLMaAY5wCi8UJGhGMWZzgjJyiEbBMxGmSpOdoHMIG4zQlGR-h-zxaPswiazqvmj7aT-e3UWjqsrbraOdKE2lnW--axviocj56e8kjpdtOtc5foLNKNcFc_uYEvc8eV9PnePH6NJ_mi1hTAW1ME-C0SkAUnIIgpah4qXjCRdaf0orzRCtSYG6g0IUmmiiWsZRQrA0lJQY6QTfDrvWV3OpaOlX_5NrJrZf5cjWXQDFk_IjuvfvoTGjlrg7aNI2yxnWhx4CllAtOevT6D7pxnbf9I1KQhFBKieghGCDtXQjeVHLv653yXxKwPKiXg3rZq5cH9fLQIUMn9KxdG38c_r_0Df4_hLM |
| CitedBy_id | crossref_primary_10_1177_0959651818771810 crossref_primary_10_3389_fnins_2024_1337580 crossref_primary_10_1007_s12555_016_0650_1 crossref_primary_10_1016_j_ymssp_2019_106335 crossref_primary_10_1007_s00521_015_1873_4 crossref_primary_10_1088_0964_1726_21_8_085015 crossref_primary_10_1007_s10846_014_0162_2 crossref_primary_10_1177_09544062211059746 crossref_primary_10_1016_j_ymssp_2018_02_004 crossref_primary_10_1002_acs_2525 crossref_primary_10_1007_s12541_016_0051_7 crossref_primary_10_3182_20130703_3_FR_4038_00054 crossref_primary_10_3390_mi12111325 crossref_primary_10_1007_s11071_016_3173_7 crossref_primary_10_1007_s12541_020_00427_4 crossref_primary_10_5772_51747 crossref_primary_10_1007_s12555_016_0721_3 crossref_primary_10_1016_j_ifacol_2023_10_1659 crossref_primary_10_1109_ACCESS_2019_2936256 crossref_primary_10_1007_s12555_011_0135_1 crossref_primary_10_1016_j_ymssp_2022_108950 crossref_primary_10_3906_elk_1309_137 crossref_primary_10_1109_LCSYS_2022_3182814 crossref_primary_10_1177_0959651814541849 crossref_primary_10_1007_s12555_014_0428_2 crossref_primary_10_1007_s12555_017_0231_y crossref_primary_10_1109_ACCESS_2018_2849994 |
| Cites_doi | 10.1016/j.sna.2006.12.011 10.1002/acs.1110 10.1016/j.matdes.2008.05.062 10.1016/S0957-4158(99)00057-4 10.1115/1.3023121 10.1109/37.588180 10.1049/el:19961085 10.1109/TMECH.2005.844709 10.1016/j.mechmat.2003.08.006 10.1088/0964-1726/12/2/310 10.1109/21.370193 10.1088/0964-1726/13/4/015 10.1007/s12555-009-0310-9 10.1117/12.203077 10.1017/S0263574797000040 10.1109/TEC.2003.821859 10.1109/ICIT.2006.372370 10.1109/TMECH.2007.901940 10.1109/91.669032 10.1109/87.701339 |
| ContentType | Journal Article |
| Copyright | Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2010 |
| Copyright_xml | – notice: Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2010 |
| DBID | AAYXX CITATION 3V. 7SC 7SP 7TB 7WY 7WZ 7XB 87Z 8AL 8FD 8FE 8FG 8FK 8FL ABUWG AFKRA ARAPS AZQEC BENPR BEZIV BGLVJ CCPQU DWQXO FR3 FRNLG F~G GNUQQ HCIFZ JQ2 K60 K6~ K7- L.- L7M L~C L~D M0C M0N P5Z P62 PQBIZ PQBZA PQEST PQQKQ PQUKI PRINS Q9U ACYCR |
| DOI | 10.1007/s12555-010-0615-8 |
| DatabaseName | CrossRef ProQuest Central (Corporate) Computer and Information Systems Abstracts Electronics & Communications Abstracts Mechanical & Transportation Engineering Abstracts ABI-INFORM Complete ABI/INFORM Global (PDF only) ProQuest Central (purchase pre-March 2016) ABI/INFORM Collection Computing Database (Alumni Edition) Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central (Alumni) (purchase pre-March 2016) ABI/INFORM Collection (Alumni Edition) ProQuest Central (Alumni) ProQuest Central Advanced Technologies & Aerospace Database (1962 - current) ProQuest Central Essentials ProQuest Central Business Premium Collection Technology Collection ProQuest One Community College ProQuest Central Engineering Research Database Business Premium Collection (Alumni) ABI/INFORM Global (Corporate) ProQuest Central Student SciTech Premium Collection (Proquest) (PQ_SDU_P3) ProQuest Computer Science Collection ProQuest Business Collection (Alumni Edition) ProQuest Business Collection Computer Science Database ABI/INFORM Professional Advanced Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional ABI/INFORM Global (ProQuest) Computing Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection One Business ProQuest One Business (Alumni) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China ProQuest Central Basic Korean Citation Index |
| DatabaseTitle | CrossRef ABI/INFORM Global (Corporate) ProQuest Business Collection (Alumni Edition) ProQuest One Business Computer Science Database ProQuest Central Student Technology Collection Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection Computer and Information Systems Abstracts ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Central China ABI/INFORM Complete ProQuest Central ABI/INFORM Professional Advanced ProQuest Central Korea Advanced Technologies Database with Aerospace ABI/INFORM Complete (Alumni Edition) Advanced Technologies & Aerospace Collection Business Premium Collection ABI/INFORM Global ProQuest Computing ABI/INFORM Global (Alumni Edition) ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest One Academic Eastern Edition Electronics & Communications Abstracts ProQuest Technology Collection ProQuest SciTech Collection ProQuest Business Collection Computer and Information Systems Abstracts Professional Advanced Technologies & Aerospace Database ProQuest One Academic UKI Edition ProQuest One Business (Alumni) Engineering Research Database ProQuest One Academic ProQuest Central (Alumni) Business Premium Collection (Alumni) |
| DatabaseTitleList | Technology Research Database ABI/INFORM Global (Corporate) |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 2005-4092 |
| EndPage | 1305 |
| ExternalDocumentID | oai_kci_go_kr_ARTI_130197 2234109311 10_1007_s12555_010_0615_8 |
| Genre | Feature |
| GroupedDBID | -EM .UV 06D 0R~ 0VY 1N0 203 29J 29~ 2KG 2LR 2VQ 30V 3V. 4.4 406 408 40D 5GY 5VS 67Z 7WY 8FE 8FG 8FL 96X 9ZL AAFGU AAHNG AAIAL AAJKR AAKPC AANZL AAPBV AARHV AARTL AATNV AATVU AAUYE AAWCG AAYFA AAYIU AAYQN AAYTO AAZMS ABDZT ABECU ABFGW ABFTD ABFTV ABJNI ABJOX ABKAS ABKCH ABMQK ABQBU ABSXP ABTEG ABTHY ABTKH ABTMW ABUWG ABXPI ACBMV ACBRV ACBYP ACGFS ACHSB ACHXU ACIGE ACIPQ ACIWK ACKNC ACMDZ ACMLO ACOKC ACTTH ACVWB ACWMK ADHHG ADHIR ADINQ ADKNI ADKPE ADMDM ADOXG ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEFTE AEGNC AEJHL AEJRE AENEX AEOHA AEPYU AESKC AESTI AETCA AEVLU AEVTX AEXYK AFGCZ AFKRA AFLOW AFNRJ AFQWF AFWTZ AFZKB AGAYW AGDGC AGGBP AGJBK AGMZJ AGQMX AGWZB AGYKE AHAVH AHBYD AHKAY AHSBF AHYZX AIAKS AIIXL AILAN AIMYW AITGF AJBLW AJDOV AJRNO AKQUC ALMA_UNASSIGNED_HOLDINGS AMKLP AMXSW AMYLF AMYQR ANMIH AOCGG ARAPS ASPBG AVWKF AXYYD AYJHY AZFZN AZQEC BA0 BENPR BEZIV BGLVJ BGNMA BPHCQ CAG CCPQU COF CSCUP DBRKI DDRTE DNIVK DPUIP DU5 DWQXO EBLON EBS EIOEI EJD ESBYG F5P FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRJ FRNLG FRRFC FSGXE FYJPI GGCAI GGRSB GJIRD GNUQQ GQ6 GQ7 GROUPED_ABI_INFORM_COMPLETE HCIFZ HF~ HG6 HLICF HMJXF HRMNR HVGLF HZ~ IKXTQ IWAJR IXC IXD I~X J-C J0Z JBSCW JZLTJ K60 K6V K6~ K7- KOV KVFHK LLZTM M0C M0N M4Y MA- NPVJJ NQJWS NU0 O9- O9J P62 P9P PQBIZ PQQKQ PROAC PT4 Q2X R9I RSV S1Z S27 S3B SDH SEG SHX SISQX SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE T13 TDB TSG U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W48 WK8 Z45 Z7R Z7S Z7X Z7Z Z83 Z88 ZMTXR ~A9 AACDK AAJBT AASML AAYXX AAYZH ABAKF ACAOD ACDTI ACZOJ AEFQL AEMSY AFBBN AGQEE AGRTI AIGIU CITATION GW5 H13 PQBZA ROL SJYHP 7SC 7SP 7TB 7XB 8AL 8FD 8FK FR3 JQ2 L.- L7M L~C L~D PQEST PQUKI PRINS Q9U ACYCR |
| ID | FETCH-LOGICAL-c381t-34173f418b73182d8f7da7478918b6f774ca2b07e1bcbc2c2a5956230ce32d013 |
| IEDL.DBID | AEJHL |
| ISSN | 1598-6446 |
| IngestDate | Tue Nov 21 21:39:09 EST 2023 Fri Oct 25 21:44:24 EDT 2024 Thu Oct 10 18:11:36 EDT 2024 Fri Nov 22 00:39:06 EST 2024 Sat Dec 16 12:03:03 EST 2023 |
| IsPeerReviewed | false |
| IsScholarly | true |
| Issue | 6 |
| Keywords | RBF neural network shape memory alloy control sliding mode control Adaptive control |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c381t-34173f418b73182d8f7da7478918b6f774ca2b07e1bcbc2c2a5956230ce32d013 |
| Notes | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 G704-000903.2010.8.6.001 |
| PQID | 824233328 |
| PQPubID | 326316 |
| PageCount | 10 |
| ParticipantIDs | nrf_kci_oai_kci_go_kr_ARTI_130197 proquest_miscellaneous_1315637872 proquest_journals_824233328 crossref_primary_10_1007_s12555_010_0615_8 springer_journals_10_1007_s12555_010_0615_8 |
| PublicationCentury | 2000 |
| PublicationDate | 2010-12-01 |
| PublicationDateYYYYMMDD | 2010-12-01 |
| PublicationDate_xml | – month: 12 year: 2010 text: 2010-12-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | Heidelberg |
| PublicationPlace_xml | – name: Heidelberg |
| PublicationSubtitle | IJCAS |
| PublicationTitle | International journal of control, automation, and systems |
| PublicationTitleAbbrev | Int. J. Control Autom. Syst |
| PublicationYear | 2010 |
| Publisher | Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers Springer Nature B.V 제어·로봇·시스템학회 |
| Publisher_xml | – name: Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers – name: Springer Nature B.V – name: 제어·로봇·시스템학회 |
| References | MadillD. R.WangD.Modeling and L2-stability of a shape memory alloy position control systemIEEE Trans. on Control Systems Technology19986447358110.1109/87.701339 MaN.SongG.LeeH.-J.Position control of shape memory alloy actuators with internal electrical resistance feedback using neural networksSmart Materials and Structures200413477778310.1088/0964-1726/13/4/015 AhnK. K.KhaN. B.Internal model control for shape memory alloy actuators using fuzzy based preisach modelSensors and Actuators A: Physical2007136273074110.1016/j.sna.2006.12.011 ChiZ.YanH.Image segmentation using fuzzy rules derived from k-means clustersJournal of Electronic Imaging19954219920610.1117/12.203077 CastrolJ. L.Fuzzy logic controllers are universal approximatorsIEEE Trans. on Systems, Man, and Cybernetics199525462963510.1109/21.370193 NascimentoM. M. S. F.de AraújoC. J.de AlmeidaL. A. L.da Rocha NetoJ. S.LimaA. M. N.A mathematical model for the strain-temperature hysteresis of shape memory alloy actuatorsMaterials and Design200930355155610.1016/j.matdes.2008.05.062 HaQ. P.Robust sliding mode controller with fuzzy tuningElectronics Letters199632171626162810.1049/el:19961085421868 LinC. M.HsuC. F.Adaptive fuzzy slidingmode control for induction servomotor systemsIEEE Trans. on Energy Conversion200419236236810.1109/TEC.2003.8218592055558 D. Suolin, Research on Robust Sliding Tracking Control for Mechano-electronic Systems with Uncertainties and Its Applications, Doctoral Thesis, Xi’an, 1999. C. L. Dimitris, Shape Memory Alloys: Modeling and Engineering Applications, Springer, 2008. ParkJ. S.HanG. S.AhnH. S.KimD. H.Adaptive approaches on the sliding mode control of robot manipulatorsTransactions on Control, Automation and Systems Engineering2001311520 AhnK. K.KhaN. B.Position control of shape memory alloy actuators using self tuning fuzzy PID controllerInternational Journal of Control, Automation, and Systems200646756762 ChenM.ChenW. H.Sliding mode control for a class of uncertain nonlinear system based on disturbance observerInternational Journal of Adaptive Control and Signal20092415164 SongG.ChaudhryV.BaturC.Precision tracking control of shape memory alloy actuators using neural networks and a sliding-mode based robust controllerSmart Materials and Structures200312222323110.1088/0964-1726/12/2/310 MohammadH. E.HashemA.Nonlinear control of a shape memory alloy actuated manipulatorTrans. of the ASME20021244566575 GoS. J.LeeM. C.ParkM. K.Design of fuzzy-sliding mode control with the self tuning fuzzy inference based on genetic algorithm and its applicationTransactions on Control, Automation and Systems Engineering2001315865 CaoJ. B.CaoB. G.Neural network sliding mode control based on on-line identification for electric vehicle with ultracapacitor-battery hybrid powerInternational Journal of Control, Automation, and Systems20097340941810.1007/s12555-009-0310-9 LagoudasD. C.EntchevP. B.Modeling of transformation-induced plasticity and its effect on the behavior of porous shape memory alloys. Part I: constitutive model for fully dense SMAsMechanics of Materials2004369865892 S. Dutta and F. Ghorbel, “Differential hysteresis modeling of a shape memory alloy wire actuator,” IEEE/ASME Trans. on Mechatronics, vol. 10, no. 2, April 2005. YooB.HamW.Adaptive fuzzy sliding mode control of nonlinear systemsIEEE Trans. on Fuzzy Systems19986231532110.1109/91.669032 AbidH.ChtourouM.ToumiA.Fuzzy indirect adaptive control scheme for nonlinear systems based on lyapunov approach and sliding modeInternational Journal of Computational Cognition2007513643 JezernikK.RodicM.SafaricR.CurkB.Neural network sliding mode controlRobotica199715233010.1017/S0263574797000040 M. Sreekumar, M. Singaperumal, T. Nagarajan, M. Zoppi, and R. Molfino, “A compliant miniature parallel manipulator with shape memory alloy actuators,” Proc. of IEEE International Conference on Industrial Technology, pp. 848–853, December 2006. R. V. P. J. Jayender and M. O. S. Nikumb, “Modelling and gain scheduled control of shape memory alloy actuators,” Proc. of the IEEE Conf. on Control Applications, pp. 767–772, August 2005. H. Ashrafiuon and V. R. Jala, “Robust control of a class of mechanical systems actuated by shape memory alloys,” ASME Journal of Dynamic Systems, Measurement and Control, vol. 131, no. 1, January 2009. ErtugrulM.KaynakO.Neuro sliding mode control of robotic manipulatorsMechatronics2000101–223926310.1016/S0957-4158(99)00057-4 KodeV. R. C.CavusogluM. C.AzarM.Design and characterization of a novel hybrid actuator using shape memory alloy and DC micro motor for minimally invasive surgery applicationsIEEE/ASME Trans Mech20072445546410.1109/TMECH.2007.901940 GrantG.HaywardV.Variable structure control of shape memory alloy actuatorsIEEE Control Systems Magazine1997173808810.1109/37.588180 K. K. Ahn (615_CR6) 2006; 4 G. Song (615_CR19) 2003; 12 H. E. Mohammad (615_CR4) 2002; 124 D. R. Madill (615_CR20) 1998; 6 615_CR5 C. M. Lin (615_CR12) 2004; 19 S. J. Go (615_CR11) 2001; 3 615_CR18 J. S. Park (615_CR13) 2001; 3 M. Ertugrul (615_CR15) 2000; 10 K. Jezernik (615_CR14) 1997; 15 M. M. S. F. Nascimento (615_CR21) 2009; 30 G. Grant (615_CR17) 1997; 17 N. Ma (615_CR8) 2004; 13 J. L. Castrol (615_CR28) 1995; 25 Z. Chi (615_CR24) 1995; 4 J. B. Cao (615_CR16) 2009; 7 V. R. C. Kode (615_CR2) 2007; 2 615_CR23 615_CR25 K. K. Ahn (615_CR7) 2007; 136 Q. P. Ha (615_CR9) 1996; 32 M. Chen (615_CR27) 2009; 24 615_CR1 615_CR3 B. Yoo (615_CR10) 1998; 6 D. C. Lagoudas (615_CR22) 2004; 36 H. Abid (615_CR26) 2007; 5 |
| References_xml | – volume: 136 start-page: 730 issue: 2 year: 2007 ident: 615_CR7 publication-title: Sensors and Actuators A: Physical doi: 10.1016/j.sna.2006.12.011 contributor: fullname: K. K. Ahn – volume: 3 start-page: 58 issue: 1 year: 2001 ident: 615_CR11 publication-title: Transactions on Control, Automation and Systems Engineering contributor: fullname: S. J. Go – volume: 24 start-page: 51 issue: 1 year: 2009 ident: 615_CR27 publication-title: International Journal of Adaptive Control and Signal doi: 10.1002/acs.1110 contributor: fullname: M. Chen – ident: 615_CR25 – volume: 3 start-page: 15 issue: 1 year: 2001 ident: 615_CR13 publication-title: Transactions on Control, Automation and Systems Engineering contributor: fullname: J. S. Park – volume: 30 start-page: 551 issue: 3 year: 2009 ident: 615_CR21 publication-title: Materials and Design doi: 10.1016/j.matdes.2008.05.062 contributor: fullname: M. M. S. F. Nascimento – volume: 10 start-page: 239 issue: 1–2 year: 2000 ident: 615_CR15 publication-title: Mechatronics doi: 10.1016/S0957-4158(99)00057-4 contributor: fullname: M. Ertugrul – ident: 615_CR18 doi: 10.1115/1.3023121 – volume: 17 start-page: 80 issue: 3 year: 1997 ident: 615_CR17 publication-title: IEEE Control Systems Magazine doi: 10.1109/37.588180 contributor: fullname: G. Grant – volume: 32 start-page: 1626 issue: 17 year: 1996 ident: 615_CR9 publication-title: Electronics Letters doi: 10.1049/el:19961085 contributor: fullname: Q. P. Ha – volume: 124 start-page: 566 issue: 4 year: 2002 ident: 615_CR4 publication-title: Trans. of the ASME contributor: fullname: H. E. Mohammad – ident: 615_CR23 doi: 10.1109/TMECH.2005.844709 – volume: 36 start-page: 865 issue: 9 year: 2004 ident: 615_CR22 publication-title: Mechanics of Materials doi: 10.1016/j.mechmat.2003.08.006 contributor: fullname: D. C. Lagoudas – volume: 12 start-page: 223 issue: 2 year: 2003 ident: 615_CR19 publication-title: Smart Materials and Structures doi: 10.1088/0964-1726/12/2/310 contributor: fullname: G. Song – volume: 4 start-page: 756 issue: 6 year: 2006 ident: 615_CR6 publication-title: International Journal of Control, Automation, and Systems contributor: fullname: K. K. Ahn – ident: 615_CR3 – volume: 25 start-page: 629 issue: 4 year: 1995 ident: 615_CR28 publication-title: IEEE Trans. on Systems, Man, and Cybernetics doi: 10.1109/21.370193 contributor: fullname: J. L. Castrol – ident: 615_CR5 – volume: 13 start-page: 777 issue: 4 year: 2004 ident: 615_CR8 publication-title: Smart Materials and Structures doi: 10.1088/0964-1726/13/4/015 contributor: fullname: N. Ma – volume: 7 start-page: 409 issue: 3 year: 2009 ident: 615_CR16 publication-title: International Journal of Control, Automation, and Systems doi: 10.1007/s12555-009-0310-9 contributor: fullname: J. B. Cao – volume: 4 start-page: 199 issue: 2 year: 1995 ident: 615_CR24 publication-title: Journal of Electronic Imaging doi: 10.1117/12.203077 contributor: fullname: Z. Chi – volume: 5 start-page: 36 issue: 1 year: 2007 ident: 615_CR26 publication-title: International Journal of Computational Cognition contributor: fullname: H. Abid – volume: 15 start-page: 23 year: 1997 ident: 615_CR14 publication-title: Robotica doi: 10.1017/S0263574797000040 contributor: fullname: K. Jezernik – volume: 19 start-page: 362 issue: 2 year: 2004 ident: 615_CR12 publication-title: IEEE Trans. on Energy Conversion doi: 10.1109/TEC.2003.821859 contributor: fullname: C. M. Lin – ident: 615_CR1 doi: 10.1109/ICIT.2006.372370 – volume: 2 start-page: 455 issue: 4 year: 2007 ident: 615_CR2 publication-title: IEEE/ASME Trans Mech doi: 10.1109/TMECH.2007.901940 contributor: fullname: V. R. C. Kode – volume: 6 start-page: 315 issue: 2 year: 1998 ident: 615_CR10 publication-title: IEEE Trans. on Fuzzy Systems doi: 10.1109/91.669032 contributor: fullname: B. Yoo – volume: 6 start-page: 473 issue: 4 year: 1998 ident: 615_CR20 publication-title: IEEE Trans. on Control Systems Technology doi: 10.1109/87.701339 contributor: fullname: D. R. Madill |
| SSID | ssj0066297 |
| Score | 2.1083531 |
| Snippet | A radial basis function neural network sliding-mode controller (RBFSMC) is proposed to control a shape memory alloy (SMA) actuator. This approach, which... |
| SourceID | nrf proquest crossref springer |
| SourceType | Open Website Aggregation Database Publisher |
| StartPage | 1296 |
| SubjectTerms | Actuators Alloys Asymptotic properties Automation Control Control systems Dynamical systems Engineering Heat transfer Kalman filters Mechatronics Neural networks Regular Papers Robotics Shape memory alloys Sheet molding compounds 제어계측공학 |
| Title | A RBF neural network sliding mode controller for SMA actuator |
| URI | https://link.springer.com/article/10.1007/s12555-010-0615-8 https://www.proquest.com/docview/824233328 https://search.proquest.com/docview/1315637872 https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART001497811 |
| Volume | 8 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| ispartofPNX | International Journal of Control, 2010, Automation, and Systems, 8(6), , pp.1296-1305 |
| link | http://sdu.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT8MwDLbYuMCBN2IMUJA4gYLWpI_0wGHApoGAAwOJW9QmKUJDHdrj_2Nv7cYQHOBUqU2tyHl8n2PHBjgJZWRSl_g8NlZw33OSK8Qp3kgzhHsvMtKSodjpRg8v6rpFaXLE7Ogi752XHsnJRj2_64bkl-LMqE6KF3BVgWUUFuDcXm62bjt35f4bhmJaUiWIFUe0D0tf5k9CFtCokg-yBaL5zTc6gZz2-n86uwFrBcFkzemM2IQll2_B6pe0g9tw0WSPl21GqSyxZT4NBGdIOAnHGNXGYUUE-7sbMGS1rHvfZAldNUELfQee262nqw4vyihwg3A84ohTkcx8T6URLmBhVRbZhNLmx_gqzJD_mUSkjch5qUmNMCIJYmJFDeOksEgRd6Ga93O3B8wGxkeKYmMn0TBLnBKO-JEMg0xYZ2QNTkt16o9ptgw9z4tMOtGoE0060aoGx6hw3TNvmnJc0_O1r3sDjUz-htxsXhzVoF4Ohy4W11Ar4oBSCpIw-4qrglwdSe764yH-jXapxM1I1OCsHKK5hF_7tP-n1nVYEbPolgOojgZjdwiVoR0fFZPyEwOT1zQ |
| link.rule.ids | 315,782,786,27933,27934,41073,42142,48344,48347,48357,49649,49652,49662,52153 |
| linkProvider | Springer Nature |
| linkToHtml | http://sdu.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV07T8MwED5ROgADb0R5GokJZKmx83AGhgItrSgMUCQ2K7EdhEApaun_565NWkAwwBQpcSzr_Pi-052_AzgOZWRSl_g8NlZw33OSK8QpXk8zhHsvMtKSo9i-j24f1WWTZHJkeRdmnO1ehiTHJ_XsshuyX0o0o0IpXsBVBap-HPq4lKuNTu-qVR7AYSgmNVWCWHGE-7AMZv7UyRc4quSD7AvT_BYcHWNOa-Vfo12F5YJissZkTazBnMvXYemT8OAGnDXY3XmLkZgltswnqeAMKSchGaPqOKzIYX91A4a8lt3fNFhCl03QR9-Eh1azd9HmRSEFbhCQ3zkiVSQz31NphFtYWJVFNiHh_BhfhRkyQJOItB45LzWpEUYkQUy8qG6cFBZJ4hbM5_3cbQOzgfGRpNjYSXTNEqeEI4YkwyAT1hlZg5PSnvptopehZ8rIZBONNtFkE61qcIQW1y_mWZPKNT2f-vploJHLdyjQ5sVRDXbL-dDF9hpqRSxQSkE9TL_ivqBgR5K7_miIf6NnKvE4EjU4Lado1sOvY9r5U-tDWGj3brq627m93oVFMc112YP598HI7UNlaEcHxQr9AAm02yQ |
| linkToPdf | http://sdu.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1ZS8QwEB5cBdEHb3E9I_ikBLdJj_RBZNVd1hPxAN9Cm6QiSlf2-P_O2NZV0QfxqdCmIUyO7xtm5gvATigjk7rE57Gxgvuek1whTvFGmiHce5GRlhzFzm109aBOWiSTc1jVwrxnu1chyaKmgVSa8sH-q832R4VvyIQp6YwuTfECrmow4aMjgwt9otk661xUh3EYiuJ-lSBWHKE_rAKbP3XyBZpqeS_7wjq_BUrf8ac9---Rz8FMST1Zs1gr8zDm8gWY_iRIuAgHTXZz1GYkcokt8yJFnCEVJYRjdGsOK3PbX1yPId9lt5dNllARCvruS3Dfbt0dd3h5wQI3CNQDjggWycz3VBrh1hZWZZFNSFA_xldhhszQJCJtRM5LTWqEEUkQE19qGCeFRfK4DON5N3crwGxgfCQvNnYSXbbEKeGIOckwyIR1RtZht7Ktfi10NPRIMZlsotEmmmyiVR220fr62TxpUr-m52NXP_c0cvxTCsB5cVSHtWpudLnt-loRO5RSUA8fX3G_UBAkyV132Me_0WOVeEyJOuxV0zXq4dcxrf6p9RZMXp-09cXp1fkaTImPFJh1GB_0hm4Dan073CwX6xv3--Pn |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+RBF+neural+network+sliding+mode+controller+for+SMA+actuator&rft.jtitle=International+journal+of+control%2C+automation%2C+and+systems&rft.au=Tai%2C+Nguyen+Trong&rft.au=Ahn%2C+Kyoung+Kwan&rft.date=2010-12-01&rft.pub=Institute+of+Control%2C+Robotics+and+Systems+and+The+Korean+Institute+of+Electrical+Engineers&rft.issn=1598-6446&rft.eissn=2005-4092&rft.volume=8&rft.issue=6&rft.spage=1296&rft.epage=1305&rft_id=info:doi/10.1007%2Fs12555-010-0615-8&rft.externalDocID=10_1007_s12555_010_0615_8 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1598-6446&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1598-6446&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1598-6446&client=summon |