Nussbaum-Based Adaptive Fuzzy Tracking Control of Unmanned Surface Vehicles with Fully Unknown Dynamics and Complex Input Nonlinearities

In this paper, subject to both fully unknown dynamics and complex input nonlinearities including unknown control directions and dead zones, a Nussbaum-based adaptive fuzzy trajectory tracking control scheme of an unmanned surface vehicle is addressed by combining adaptive fuzzy backstepping techniqu...

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Published inInternational journal of fuzzy systems Vol. 20; no. 1; pp. 259 - 268
Main Authors Wang, Ning, Gao, Ying, Sun, Zhuo, Zheng, Zhongjiu
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2018
Springer Nature B.V
Subjects
Adaptive control
Approximation
Artificial Intelligence
Closed loops
Computational Intelligence
Controllers
Design
Engineering
Fluid mechanics
Fuzzy control
Fuzzy logic
Management Science
Neural networks
Nonlinearity
Operations Research
Surface vehicles
Systems stability
Tracking control
Tracking errors
Tracking systems
Trajectory control
Uncertainty
Unmanned vehicles
Adaptive fuzzy control
Fully unknown dynamics
Complex input nonlinearities
Unmanned surface vehicles
Fuzzy approximation
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Abstract In this paper, subject to both fully unknown dynamics and complex input nonlinearities including unknown control directions and dead zones, a Nussbaum-based adaptive fuzzy trajectory tracking control scheme of an unmanned surface vehicle is addressed by combining adaptive fuzzy backstepping technique with Nussbaum approach. The dead-zone input nonlinearity is firstly divided into input-dependent functions and time-varying input coefficients which can be treated as system uncertainties. Together with disturbances, unknown dynamics and uncertainties, the lumped nonlinearity is online approximated by employing an adaptive fuzzy approximator. Within the backstepping framework, a Nussbaum gain function is further designed to tackle unknown control directions, and thereby devising an adaptive fuzzy trajectory tracking control scheme which is constructed recursively to deal with complex input nonlinearities and fully unknown dynamics. Theoretical analysis reveals that all signals of the closed-loop tracking system are bounded and tracking errors can converge to an arbitrarily small neighborhood of zero. Simulation studies demonstrate the effectiveness and superiority of the proposed approach.
AbstractList In this paper, subject to both fully unknown dynamics and complex input nonlinearities including unknown control directions and dead zones, a Nussbaum-based adaptive fuzzy trajectory tracking control scheme of an unmanned surface vehicle is addressed by combining adaptive fuzzy backstepping technique with Nussbaum approach. The dead-zone input nonlinearity is firstly divided into input-dependent functions and time-varying input coefficients which can be treated as system uncertainties. Together with disturbances, unknown dynamics and uncertainties, the lumped nonlinearity is online approximated by employing an adaptive fuzzy approximator. Within the backstepping framework, a Nussbaum gain function is further designed to tackle unknown control directions, and thereby devising an adaptive fuzzy trajectory tracking control scheme which is constructed recursively to deal with complex input nonlinearities and fully unknown dynamics. Theoretical analysis reveals that all signals of the closed-loop tracking system are bounded and tracking errors can converge to an arbitrarily small neighborhood of zero. Simulation studies demonstrate the effectiveness and superiority of the proposed approach.
Author Gao, Ying
Wang, Ning
Sun, Zhuo
Zheng, Zhongjiu
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  orcidid: 0000-0003-1745-1425
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  givenname: Ying
  surname: Gao
  fullname: Gao, Ying
  organization: Center for Intelligent Marine Vehicles, and School of Marine Electrical Engineering, Dalian Maritime University
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  givenname: Zhuo
  surname: Sun
  fullname: Sun, Zhuo
  organization: Center for Intelligent Marine Vehicles, and School of Marine Electrical Engineering, Dalian Maritime University
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  givenname: Zhongjiu
  surname: Zheng
  fullname: Zheng, Zhongjiu
  organization: Center for Intelligent Marine Vehicles, and School of Marine Electrical Engineering, Dalian Maritime University
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Cites_doi 10.1016/j.automatica.2015.12.026
10.1109/TCST.2014.2359880
10.1109/TCST.2015.2510587
10.1007/s40815-015-0071-y
10.1109/TFUZZ.2013.2291562
10.1109/TCYB.2015.2411285
10.3390/s16081335
10.1109/TIV.2017.2657379
10.4031/MTSJ.50.1.4
10.1007/0-8176-4470-9_23
10.1109/TNN.2010.2042611
10.1109/TSMC.2015.2429555
10.1109/TCYB.2015.2423635
10.1016/j.robot.2016.01.005
10.1109/TCST.2010.2090526
10.1049/iet-cta.2011.0176
10.1016/j.automatica.2017.02.026
10.1109/87.852916
10.1109/TFUZZ.2014.2362144
10.1109/TCYB.2014.2382679
10.1109/TCYB.2015.2451116
10.1016/j.cor.2016.09.017
10.1109/TCST.2013.2281211
10.1016/j.automatica.2009.03.010
10.1109/TNNLS.2013.2296048
10.1109/TFUZZ.2013.2291554
10.1109/TNNLS.2014.2334366
10.1109/TCST.2015.2496585
10.1109/TNN.2008.2010349
10.1109/TII.2012.2219541
10.1109/TNNLS.2017.2665581
10.1109/TFUZZ.2014.2348017
10.1016/j.neucom.2015.10.016
10.1016/j.neucom.2015.11.017
10.1016/j.fss.2015.04.005
10.1016/j.robot.2014.09.024
10.1016/j.sysconle.2015.07.002
10.1016/j.automatica.2004.10.006
10.1109/TFUZZ.2017.2697399
10.1109/TII.2016.2608739
10.1109/TNNLS.2016.2544786
10.1016/j.fss.2009.04.011
10.1016/j.apor.2015.09.010
10.1007/s40815-015-0015-6
10.1007/s11071-015-1958-8
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Keywords Adaptive fuzzy control
Fully unknown dynamics
Complex input nonlinearities
Unmanned surface vehicles
Fuzzy approximation
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References GaoYTongSCComposite adaptive fuzzy output feedback dynamic surface control design for stochastic large-scale nonlinear systems with unknown dead zoneNeurocomputing2015175556410.1016/j.neucom.2015.10.016
XiangXBYuCYZhangQRobust fuzzy 3D path following for autonomous underwater vehicle subject to uncertaintiesComput. Oper. Res.201784165177363801510.1016/j.cor.2016.09.017
ZhangRChenYSunFXuHPath control of a surface ship in restricted water using sliding modeIEEE Trans. Control Syst. Technol.20008472273210.1109/87.852916
SlotineJJELiWApplied Nonlinear Control1991Englewood CliffsPrentice Hall0753.93036
WangNErMJHanMParsimonious extreme learning machine using recursive orthogonal least squaresIEEE Trans. Neural Netw. Learn. Syst.201425101828184110.1109/TNNLS.2013.2296048
HeWChenYHYinZAdaptive neural network control of an uncertain robot with full-state constraintsIEEE Trans. Cybernet.201646362062910.1109/TCYB.2015.2411285
WangNErMJHanMLarge tanker motion model identification using generalized ellipsoidal basis function-based fuzzy neural networksIEEE Trans. Cybernet.201545122732274310.1109/TCYB.2014.2382679
XuBRobust adaptive neural control of flexible hypersonic flight vehicle with dead-zone input nonlinearityNonlinear Dyn.201580315091520333440210.1007/s11071-015-1958-81351.93102
ChuZZZhuDQYangSXObserver-based adaptive neural network trajectory tracking control for remotely operated vehicleIEEE Trans. Neural Netw. Learn. Syst.20173666186
XiangXBLapierreLJouvencelBSmooth transition of AUV motion control: from fully-actuated to under-actuated configurationRobot. Auton. Syst.2015675142210.1016/j.robot.2014.09.024
WangNSunJCErMJLiuYCA novel extreme learning control framework of unmanned surface vehiclesIEEE Trans. Cybernet.20164651106111710.1109/TCYB.2015.2423635
BoulkrouneATadjineMSaadMFarzaMFuzzy adaptive controller for MIMO nonlinear systems with known and unknown control directionFuzzy Sets Syst.20101616797820258559810.1016/j.fss.2009.04.0111217.93086
LiZSunJOhSDesign, analysis and experimental validation of a robust nonlinear path following controller for marine surface vesselsAutomatica200945716491658287947810.1016/j.automatica.2009.03.0101184.93038
HeWDongYTAdaptive fuzzy neural network control for a constrained robot using impedance learningIEEE Trans. Neural Netw. Learn. Syst.2017
ZhengZSunLPath following control for marine surface vessel with uncertainties and input saturationNeurocomputing2016177115816710.1016/j.neucom.2015.11.017
GaoYTongSCComposite adaptive fuzzy output feedback dynamic surface control design for uncertain nonlinear stochastic systems with input quantizationInt. J. Fuzzy Syst.2015174609622342204910.1007/s40815-015-0071-y
KhalilHNonlinear Systems19962Upper Saddle RiverPrentice-Hall Press
ShojaeiKNeural adaptive robust control of underactuated marine surfacevehicles with input saturationAppl. Ocean Res.201553426727810.1016/j.apor.2015.09.010
ShojaeiKObserver-based neural adaptive formation control of autonomous surface vessels with limited torqueRobot. Auton. Syst.2016781839610.1016/j.robot.2016.01.005
GaoYTongSCLiYMObserver-based adaptive fuzzy output constrained control for MIMO nonlinear systems with unknown control directionsFuzzy Sets Syst.201629017999346025210.1016/j.fss.2015.04.0051374.93211
TongSCSuiSLiYMAdaptive fuzzy decentralized output stabilization for stochastic nonlinear large-scale systems with unknown control directionsIEEE Trans. Fuzzy Syst.20142251365137210.1109/TFUZZ.2013.2291554
WangNSunJCErMJTracking-error-based universal adaptive fuzzy control for output tracking of nonlinear systems with completely unknown dynamicsIEEE Trans. Fuzzy Syst.2017
ZhangTPGeSSAdaptive neural network tracking control of MIMO nonlinear systems with unknown dead zones and control directionsIEEE Trans. Neural Netw.200920348349310.1109/TNN.2008.2010349
HeWDongYTSunCYAdaptive neural impedance control of a robotic manipulator with input saturationIEEE Trans. Syst. Man Cybernet. Syst.201646333434410.1109/TSMC.2015.2429555
HuangJWenCWangWSongYDGlobal stable tracking control of underactuated ships with input saturationSyst. Control Lett.201585117341714610.1016/j.sysconle.2015.07.0021322.93050
WangNQianCSunZYGlobal asymptotic output tracking of nonlinear second-order systems with power integratorsAutomatica2017801156161363806810.1016/j.automatica.2017.02.0261370.93082
WangNErMJSelf-constructing adaptive robust fuzzy neural tracking control of surface vehicles with uncertainties and unknown disturbancesIEEE Trans. Control Syst. Technol.2015233991100210.1109/TCST.2014.2359880
HeWGeSSCooperative control of a nonuniform gantry crane with constrained tensionAutomatica2016664146154345842310.1016/j.automatica.2015.12.0261335.93012
FossenTIMarine Control Systems: Guidance. Navigation and Control of Ships, Rigs and Underwater Vehicles2002TrondheimMarine Cybernetics
XiangXBYuCYNiuZMZhangQSubsea cable tracking by autonomous underwater vehicle with magnetic sensing guidanceSensors2016168133510.3390/s16081335
ZhangQLapierreLXiangXBDistributed control of coordinated path tracking for networked nonholonomic mobile vehiclesIEEE Trans. Ind. Inform.20139147248410.1109/TII.2012.2219541
YuRZhuQXiaGLiuZSliding mode tracking control of an underactuated surface vesselIET Control Theory Appl.201263461466295187910.1049/iet-cta.2011.0176
BoldbaatarEALinCMSelf-learning fuzzy sliding-mode control for a water bath temperature control systemInt. J. Fuzzy Syst.2015171313810.1007/s40815-015-0015-6
XiangXBYuCYZhangQXuGHPath-following control of an AUV: Fully actuated versus under-actuated configurationMar. Technol. Soc. J.2016501344710.4031/MTSJ.50.1.4
WangNErMJDirect adaptive fuzzy tracking control of marine vehicle with fully unknown parametric dynamics and uncertaintiesIEEE Trans. Control Syst. Technol.20162451845185210.1109/TCST.2015.2510587
HarmoucheMLaghroucheSChitourYGlobal tracking for underactuated ships with bounded feedback controllersInt. J. Control201487102035204332543941308.93091
WangNQianCSunJCLiuYCAdaptive robust finite-time trajectory tracking control of fully actuated marine surface vehiclesIEEE Trans. Control Syst. Technol.20162441454146210.1109/TCST.2015.2496585
ChenMGeSSVoon Ee HowBRobust adaptive neural network control for a class of uncertain MIMO nonlinear systems with input nonlinearitiesIEEE Trans. Neural Netw.201021579681210.1109/TNN.2010.2042611
SkjetneRFossenTIKokotovicPVAdaptive maneuvering with experiments, for a model ships in a marine control laboratoryAutomatica2005412289298215766410.1016/j.automatica.2004.10.0061096.93026
WangNErMJHanMDynamic tanker steering control using generalized-ellipsoidal-basis-function-based fuzzy neural networksIEEE Trans. Fuzzy Syst.20152351414142710.1109/TFUZZ.2014.2362144
HeWOuyangYCHongJVibration control of a flexible robotic manipulator in the presence of input deadzoneIEEE Trans. Ind. Inform.2017131485910.1109/TII.2016.2608739
ShiWXAdaptive fuzzy control for MIMO nonlinear systems with nonsymmetric control gain matrix and unknown control directionIEEE Trans. Fuzzy Syst.20142251288123010.1109/TFUZZ.2013.2291562
WangNErMJHanMGeneralized single-hidden layer feedforward networks for regression problemsIEEE Trans. Neural Netw. Learn. Syst.201526611611176345484010.1109/TNNLS.2014.2334366
ChwaDGlobal tracking control of underactuated ships with input and velocity constraints using dynamic surface control methodIEEE Trans. Control Syst. Technol.20111961357137010.1109/TCST.2010.2090526
LiYMTongSCLiTSObserver-based adaptive fuzzy tracking control of MIMO stochastic nonlinear systems with unknown control directions and unknown dead-zonesIEEE Trans. Fuzzy Syst.20152341228124110.1109/TFUZZ.2014.2348017
WangNErMJSunJCLiuYCAdaptive robust online constructive fuzzy control of a complex surface vehicle systemIEEE Trans. Cybernet.20164671511152310.1109/TCYB.2015.2451116
LeonessaAVanZwietenTMorelYMeniniLZaccarianLAbdallahCNeural network model reference adaptive control of marine vehiclesCurrent Trends in Nonlinear Systems and Control2006Birkhäuser BostonSpringer42144010.1007/0-8176-4470-9_23
ZhaoZHeWGeSSAdaptive neural network control of a fully actuated marine surface vessel with multiple output constraintsIEEE Trans. Control Syst. Technol.2014221536154310.1109/TCST.2013.2281211
WangNLvSLErMJChenWHFast and accurate trajectory tracking control of an autonomous surface vehicle with unmodeled dynamics and disturbancesIEEE Trans. Intell. Veh.20161323024310.1109/TIV.2017.2657379
W He (387_CR22) 2017
N Wang (387_CR46) 2015; 26
EA Boldbaatar (387_CR17) 2015; 17
M Harmouche (387_CR32) 2014; 87
B Xu (387_CR37) 2015; 80
JJE Slotine (387_CR15) 1991
A Boulkroune (387_CR42) 2010; 161
N Wang (387_CR26) 2016; 24
YM Li (387_CR40) 2015; 23
Y Gao (387_CR41) 2015; 175
Z Li (387_CR12) 2009; 45
ZZ Chu (387_CR23) 2017
Z Zheng (387_CR31) 2016; 177
R Zhang (387_CR16) 2000; 8
XB Xiang (387_CR5) 2016; 16
TP Zhang (387_CR44) 2009; 20
XB Xiang (387_CR8) 2015; 67
N Wang (387_CR47) 2014; 25
M Chen (387_CR13) 2010; 21
R Skjetne (387_CR49) 2005; 41
Z Zhao (387_CR25) 2014; 22
Y Gao (387_CR48) 2015; 17
TI Fossen (387_CR1) 2002
XB Xiang (387_CR9) 2016; 50
K Shojaei (387_CR35) 2016; 78
N Wang (387_CR2) 2015; 23
N Wang (387_CR6) 2017; 80
W He (387_CR21) 2016; 46
W He (387_CR4) 2016; 66
N Wang (387_CR19) 2016; 46
N Wang (387_CR7) 2017
Y Gao (387_CR39) 2016; 290
K Shojaei (387_CR34) 2015; 53
SC Tong (387_CR45) 2014; 22
XB Xiang (387_CR14) 2017; 84
W He (387_CR36) 2017; 13
N Wang (387_CR3) 2015; 45
N Wang (387_CR29) 2016; 24
N Wang (387_CR28) 2015; 23
N Wang (387_CR24) 2016; 46
WX Shi (387_CR43) 2014; 22
H Khalil (387_CR11) 1996
J Huang (387_CR33) 2015; 85
W He (387_CR20) 2016; 46
R Yu (387_CR18) 2012; 6
Q Zhang (387_CR10) 2013; 9
D Chwa (387_CR30) 2011; 19
A Leonessa (387_CR27) 2006
N Wang (387_CR38) 2016; 1
References_xml – reference: HuangJWenCWangWSongYDGlobal stable tracking control of underactuated ships with input saturationSyst. Control Lett.201585117341714610.1016/j.sysconle.2015.07.0021322.93050
– reference: HeWGeSSCooperative control of a nonuniform gantry crane with constrained tensionAutomatica2016664146154345842310.1016/j.automatica.2015.12.0261335.93012
– reference: WangNErMJDirect adaptive fuzzy tracking control of marine vehicle with fully unknown parametric dynamics and uncertaintiesIEEE Trans. Control Syst. Technol.20162451845185210.1109/TCST.2015.2510587
– reference: ZhangTPGeSSAdaptive neural network tracking control of MIMO nonlinear systems with unknown dead zones and control directionsIEEE Trans. Neural Netw.200920348349310.1109/TNN.2008.2010349
– reference: WangNSunJCErMJTracking-error-based universal adaptive fuzzy control for output tracking of nonlinear systems with completely unknown dynamicsIEEE Trans. Fuzzy Syst.2017
– reference: ChuZZZhuDQYangSXObserver-based adaptive neural network trajectory tracking control for remotely operated vehicleIEEE Trans. Neural Netw. Learn. Syst.20173666186
– reference: HarmoucheMLaghroucheSChitourYGlobal tracking for underactuated ships with bounded feedback controllersInt. J. Control201487102035204332543941308.93091
– reference: HeWOuyangYCHongJVibration control of a flexible robotic manipulator in the presence of input deadzoneIEEE Trans. Ind. Inform.2017131485910.1109/TII.2016.2608739
– reference: HeWDongYTSunCYAdaptive neural impedance control of a robotic manipulator with input saturationIEEE Trans. Syst. Man Cybernet. Syst.201646333434410.1109/TSMC.2015.2429555
– reference: WangNErMJHanMParsimonious extreme learning machine using recursive orthogonal least squaresIEEE Trans. Neural Netw. Learn. Syst.201425101828184110.1109/TNNLS.2013.2296048
– reference: HeWChenYHYinZAdaptive neural network control of an uncertain robot with full-state constraintsIEEE Trans. Cybernet.201646362062910.1109/TCYB.2015.2411285
– reference: XiangXBYuCYZhangQXuGHPath-following control of an AUV: Fully actuated versus under-actuated configurationMar. Technol. Soc. J.2016501344710.4031/MTSJ.50.1.4
– reference: BoulkrouneATadjineMSaadMFarzaMFuzzy adaptive controller for MIMO nonlinear systems with known and unknown control directionFuzzy Sets Syst.20101616797820258559810.1016/j.fss.2009.04.0111217.93086
– reference: WangNLvSLErMJChenWHFast and accurate trajectory tracking control of an autonomous surface vehicle with unmodeled dynamics and disturbancesIEEE Trans. Intell. Veh.20161323024310.1109/TIV.2017.2657379
– reference: WangNQianCSunJCLiuYCAdaptive robust finite-time trajectory tracking control of fully actuated marine surface vehiclesIEEE Trans. Control Syst. Technol.20162441454146210.1109/TCST.2015.2496585
– reference: GaoYTongSCComposite adaptive fuzzy output feedback dynamic surface control design for stochastic large-scale nonlinear systems with unknown dead zoneNeurocomputing2015175556410.1016/j.neucom.2015.10.016
– reference: ChenMGeSSVoon Ee HowBRobust adaptive neural network control for a class of uncertain MIMO nonlinear systems with input nonlinearitiesIEEE Trans. Neural Netw.201021579681210.1109/TNN.2010.2042611
– reference: XiangXBLapierreLJouvencelBSmooth transition of AUV motion control: from fully-actuated to under-actuated configurationRobot. Auton. Syst.2015675142210.1016/j.robot.2014.09.024
– reference: WangNSunJCErMJLiuYCA novel extreme learning control framework of unmanned surface vehiclesIEEE Trans. Cybernet.20164651106111710.1109/TCYB.2015.2423635
– reference: GaoYTongSCComposite adaptive fuzzy output feedback dynamic surface control design for uncertain nonlinear stochastic systems with input quantizationInt. J. Fuzzy Syst.2015174609622342204910.1007/s40815-015-0071-y
– reference: WangNErMJHanMDynamic tanker steering control using generalized-ellipsoidal-basis-function-based fuzzy neural networksIEEE Trans. Fuzzy Syst.20152351414142710.1109/TFUZZ.2014.2362144
– reference: ShojaeiKObserver-based neural adaptive formation control of autonomous surface vessels with limited torqueRobot. Auton. Syst.2016781839610.1016/j.robot.2016.01.005
– reference: LiYMTongSCLiTSObserver-based adaptive fuzzy tracking control of MIMO stochastic nonlinear systems with unknown control directions and unknown dead-zonesIEEE Trans. Fuzzy Syst.20152341228124110.1109/TFUZZ.2014.2348017
– reference: WangNErMJHanMGeneralized single-hidden layer feedforward networks for regression problemsIEEE Trans. Neural Netw. Learn. Syst.201526611611176345484010.1109/TNNLS.2014.2334366
– reference: ShojaeiKNeural adaptive robust control of underactuated marine surfacevehicles with input saturationAppl. Ocean Res.201553426727810.1016/j.apor.2015.09.010
– reference: XuBRobust adaptive neural control of flexible hypersonic flight vehicle with dead-zone input nonlinearityNonlinear Dyn.201580315091520333440210.1007/s11071-015-1958-81351.93102
– reference: ZhangQLapierreLXiangXBDistributed control of coordinated path tracking for networked nonholonomic mobile vehiclesIEEE Trans. Ind. Inform.20139147248410.1109/TII.2012.2219541
– reference: LeonessaAVanZwietenTMorelYMeniniLZaccarianLAbdallahCNeural network model reference adaptive control of marine vehiclesCurrent Trends in Nonlinear Systems and Control2006Birkhäuser BostonSpringer42144010.1007/0-8176-4470-9_23
– reference: TongSCSuiSLiYMAdaptive fuzzy decentralized output stabilization for stochastic nonlinear large-scale systems with unknown control directionsIEEE Trans. Fuzzy Syst.20142251365137210.1109/TFUZZ.2013.2291554
– reference: SlotineJJELiWApplied Nonlinear Control1991Englewood CliffsPrentice Hall0753.93036
– reference: HeWDongYTAdaptive fuzzy neural network control for a constrained robot using impedance learningIEEE Trans. Neural Netw. Learn. Syst.2017
– reference: WangNErMJSelf-constructing adaptive robust fuzzy neural tracking control of surface vehicles with uncertainties and unknown disturbancesIEEE Trans. Control Syst. Technol.2015233991100210.1109/TCST.2014.2359880
– reference: KhalilHNonlinear Systems19962Upper Saddle RiverPrentice-Hall Press
– reference: ZhaoZHeWGeSSAdaptive neural network control of a fully actuated marine surface vessel with multiple output constraintsIEEE Trans. Control Syst. Technol.2014221536154310.1109/TCST.2013.2281211
– reference: WangNErMJSunJCLiuYCAdaptive robust online constructive fuzzy control of a complex surface vehicle systemIEEE Trans. Cybernet.20164671511152310.1109/TCYB.2015.2451116
– reference: WangNQianCSunZYGlobal asymptotic output tracking of nonlinear second-order systems with power integratorsAutomatica2017801156161363806810.1016/j.automatica.2017.02.0261370.93082
– reference: ChwaDGlobal tracking control of underactuated ships with input and velocity constraints using dynamic surface control methodIEEE Trans. Control Syst. Technol.20111961357137010.1109/TCST.2010.2090526
– reference: GaoYTongSCLiYMObserver-based adaptive fuzzy output constrained control for MIMO nonlinear systems with unknown control directionsFuzzy Sets Syst.201629017999346025210.1016/j.fss.2015.04.0051374.93211
– reference: LiZSunJOhSDesign, analysis and experimental validation of a robust nonlinear path following controller for marine surface vesselsAutomatica200945716491658287947810.1016/j.automatica.2009.03.0101184.93038
– reference: XiangXBYuCYNiuZMZhangQSubsea cable tracking by autonomous underwater vehicle with magnetic sensing guidanceSensors2016168133510.3390/s16081335
– reference: ZhangRChenYSunFXuHPath control of a surface ship in restricted water using sliding modeIEEE Trans. Control Syst. Technol.20008472273210.1109/87.852916
– reference: ZhengZSunLPath following control for marine surface vessel with uncertainties and input saturationNeurocomputing2016177115816710.1016/j.neucom.2015.11.017
– reference: BoldbaatarEALinCMSelf-learning fuzzy sliding-mode control for a water bath temperature control systemInt. J. Fuzzy Syst.2015171313810.1007/s40815-015-0015-6
– reference: FossenTIMarine Control Systems: Guidance. Navigation and Control of Ships, Rigs and Underwater Vehicles2002TrondheimMarine Cybernetics
– reference: WangNErMJHanMLarge tanker motion model identification using generalized ellipsoidal basis function-based fuzzy neural networksIEEE Trans. Cybernet.201545122732274310.1109/TCYB.2014.2382679
– reference: YuRZhuQXiaGLiuZSliding mode tracking control of an underactuated surface vesselIET Control Theory Appl.201263461466295187910.1049/iet-cta.2011.0176
– reference: XiangXBYuCYZhangQRobust fuzzy 3D path following for autonomous underwater vehicle subject to uncertaintiesComput. Oper. Res.201784165177363801510.1016/j.cor.2016.09.017
– reference: ShiWXAdaptive fuzzy control for MIMO nonlinear systems with nonsymmetric control gain matrix and unknown control directionIEEE Trans. Fuzzy Syst.20142251288123010.1109/TFUZZ.2013.2291562
– reference: SkjetneRFossenTIKokotovicPVAdaptive maneuvering with experiments, for a model ships in a marine control laboratoryAutomatica2005412289298215766410.1016/j.automatica.2004.10.0061096.93026
– volume: 66
  start-page: 146
  issue: 4
  year: 2016
  ident: 387_CR4
  publication-title: Automatica
  doi: 10.1016/j.automatica.2015.12.026
– volume: 23
  start-page: 991
  issue: 3
  year: 2015
  ident: 387_CR28
  publication-title: IEEE Trans. Control Syst. Technol.
  doi: 10.1109/TCST.2014.2359880
– volume: 24
  start-page: 1845
  issue: 5
  year: 2016
  ident: 387_CR29
  publication-title: IEEE Trans. Control Syst. Technol.
  doi: 10.1109/TCST.2015.2510587
– volume: 17
  start-page: 609
  issue: 4
  year: 2015
  ident: 387_CR48
  publication-title: Int. J. Fuzzy Syst.
  doi: 10.1007/s40815-015-0071-y
– volume: 22
  start-page: 1288
  issue: 5
  year: 2014
  ident: 387_CR43
  publication-title: IEEE Trans. Fuzzy Syst.
  doi: 10.1109/TFUZZ.2013.2291562
– volume: 46
  start-page: 620
  issue: 3
  year: 2016
  ident: 387_CR20
  publication-title: IEEE Trans. Cybernet.
  doi: 10.1109/TCYB.2015.2411285
– volume: 16
  start-page: 1335
  issue: 8
  year: 2016
  ident: 387_CR5
  publication-title: Sensors
  doi: 10.3390/s16081335
– volume: 1
  start-page: 230
  issue: 3
  year: 2016
  ident: 387_CR38
  publication-title: IEEE Trans. Intell. Veh.
  doi: 10.1109/TIV.2017.2657379
– volume: 50
  start-page: 34
  issue: 1
  year: 2016
  ident: 387_CR9
  publication-title: Mar. Technol. Soc. J.
  doi: 10.4031/MTSJ.50.1.4
– start-page: 421
  volume-title: Current Trends in Nonlinear Systems and Control
  year: 2006
  ident: 387_CR27
  doi: 10.1007/0-8176-4470-9_23
– volume: 21
  start-page: 796
  issue: 5
  year: 2010
  ident: 387_CR13
  publication-title: IEEE Trans. Neural Netw.
  doi: 10.1109/TNN.2010.2042611
– volume: 46
  start-page: 334
  issue: 3
  year: 2016
  ident: 387_CR21
  publication-title: IEEE Trans. Syst. Man Cybernet. Syst.
  doi: 10.1109/TSMC.2015.2429555
– volume: 46
  start-page: 1106
  issue: 5
  year: 2016
  ident: 387_CR19
  publication-title: IEEE Trans. Cybernet.
  doi: 10.1109/TCYB.2015.2423635
– volume: 78
  start-page: 83
  issue: 1
  year: 2016
  ident: 387_CR35
  publication-title: Robot. Auton. Syst.
  doi: 10.1016/j.robot.2016.01.005
– volume: 19
  start-page: 1357
  issue: 6
  year: 2011
  ident: 387_CR30
  publication-title: IEEE Trans. Control Syst. Technol.
  doi: 10.1109/TCST.2010.2090526
– volume: 6
  start-page: 461
  issue: 3
  year: 2012
  ident: 387_CR18
  publication-title: IET Control Theory Appl.
  doi: 10.1049/iet-cta.2011.0176
– volume: 87
  start-page: 2035
  issue: 10
  year: 2014
  ident: 387_CR32
  publication-title: Int. J. Control
– volume: 80
  start-page: 156
  issue: 1
  year: 2017
  ident: 387_CR6
  publication-title: Automatica
  doi: 10.1016/j.automatica.2017.02.026
– volume: 8
  start-page: 722
  issue: 4
  year: 2000
  ident: 387_CR16
  publication-title: IEEE Trans. Control Syst. Technol.
  doi: 10.1109/87.852916
– volume: 23
  start-page: 1414
  issue: 5
  year: 2015
  ident: 387_CR2
  publication-title: IEEE Trans. Fuzzy Syst.
  doi: 10.1109/TFUZZ.2014.2362144
– volume: 45
  start-page: 2732
  issue: 12
  year: 2015
  ident: 387_CR3
  publication-title: IEEE Trans. Cybernet.
  doi: 10.1109/TCYB.2014.2382679
– volume: 46
  start-page: 1511
  issue: 7
  year: 2016
  ident: 387_CR24
  publication-title: IEEE Trans. Cybernet.
  doi: 10.1109/TCYB.2015.2451116
– volume: 84
  start-page: 165
  year: 2017
  ident: 387_CR14
  publication-title: Comput. Oper. Res.
  doi: 10.1016/j.cor.2016.09.017
– volume: 22
  start-page: 1536
  year: 2014
  ident: 387_CR25
  publication-title: IEEE Trans. Control Syst. Technol.
  doi: 10.1109/TCST.2013.2281211
– volume: 45
  start-page: 1649
  issue: 7
  year: 2009
  ident: 387_CR12
  publication-title: Automatica
  doi: 10.1016/j.automatica.2009.03.010
– volume: 25
  start-page: 1828
  issue: 10
  year: 2014
  ident: 387_CR47
  publication-title: IEEE Trans. Neural Netw. Learn. Syst.
  doi: 10.1109/TNNLS.2013.2296048
– volume: 22
  start-page: 1365
  issue: 5
  year: 2014
  ident: 387_CR45
  publication-title: IEEE Trans. Fuzzy Syst.
  doi: 10.1109/TFUZZ.2013.2291554
– volume-title: Marine Control Systems: Guidance. Navigation and Control of Ships, Rigs and Underwater Vehicles
  year: 2002
  ident: 387_CR1
– volume: 26
  start-page: 1161
  issue: 6
  year: 2015
  ident: 387_CR46
  publication-title: IEEE Trans. Neural Netw. Learn. Syst.
  doi: 10.1109/TNNLS.2014.2334366
– volume-title: Applied Nonlinear Control
  year: 1991
  ident: 387_CR15
– volume: 24
  start-page: 1454
  issue: 4
  year: 2016
  ident: 387_CR26
  publication-title: IEEE Trans. Control Syst. Technol.
  doi: 10.1109/TCST.2015.2496585
– volume: 20
  start-page: 483
  issue: 3
  year: 2009
  ident: 387_CR44
  publication-title: IEEE Trans. Neural Netw.
  doi: 10.1109/TNN.2008.2010349
– volume: 9
  start-page: 472
  issue: 1
  year: 2013
  ident: 387_CR10
  publication-title: IEEE Trans. Ind. Inform.
  doi: 10.1109/TII.2012.2219541
– year: 2017
  ident: 387_CR22
  publication-title: IEEE Trans. Neural Netw. Learn. Syst.
  doi: 10.1109/TNNLS.2017.2665581
– volume: 23
  start-page: 1228
  issue: 4
  year: 2015
  ident: 387_CR40
  publication-title: IEEE Trans. Fuzzy Syst.
  doi: 10.1109/TFUZZ.2014.2348017
– volume: 175
  start-page: 55
  year: 2015
  ident: 387_CR41
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2015.10.016
– volume: 177
  start-page: 158
  issue: 1
  year: 2016
  ident: 387_CR31
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2015.11.017
– volume: 290
  start-page: 79
  issue: 1
  year: 2016
  ident: 387_CR39
  publication-title: Fuzzy Sets Syst.
  doi: 10.1016/j.fss.2015.04.005
– volume: 67
  start-page: 14
  issue: 5
  year: 2015
  ident: 387_CR8
  publication-title: Robot. Auton. Syst.
  doi: 10.1016/j.robot.2014.09.024
– volume: 85
  start-page: 1
  issue: 1
  year: 2015
  ident: 387_CR33
  publication-title: Syst. Control Lett.
  doi: 10.1016/j.sysconle.2015.07.002
– volume: 41
  start-page: 289
  issue: 2
  year: 2005
  ident: 387_CR49
  publication-title: Automatica
  doi: 10.1016/j.automatica.2004.10.006
– year: 2017
  ident: 387_CR7
  publication-title: IEEE Trans. Fuzzy Syst.
  doi: 10.1109/TFUZZ.2017.2697399
– volume-title: Nonlinear Systems
  year: 1996
  ident: 387_CR11
– volume: 13
  start-page: 48
  issue: 1
  year: 2017
  ident: 387_CR36
  publication-title: IEEE Trans. Ind. Inform.
  doi: 10.1109/TII.2016.2608739
– year: 2017
  ident: 387_CR23
  publication-title: IEEE Trans. Neural Netw. Learn. Syst.
  doi: 10.1109/TNNLS.2016.2544786
– volume: 161
  start-page: 797
  issue: 6
  year: 2010
  ident: 387_CR42
  publication-title: Fuzzy Sets Syst.
  doi: 10.1016/j.fss.2009.04.011
– volume: 53
  start-page: 267
  issue: 4
  year: 2015
  ident: 387_CR34
  publication-title: Appl. Ocean Res.
  doi: 10.1016/j.apor.2015.09.010
– volume: 17
  start-page: 31
  issue: 1
  year: 2015
  ident: 387_CR17
  publication-title: Int. J. Fuzzy Syst.
  doi: 10.1007/s40815-015-0015-6
– volume: 80
  start-page: 1509
  issue: 3
  year: 2015
  ident: 387_CR37
  publication-title: Nonlinear Dyn.
  doi: 10.1007/s11071-015-1958-8
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Snippet In this paper, subject to both fully unknown dynamics and complex input nonlinearities including unknown control directions and dead zones, a Nussbaum-based...
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SubjectTerms Adaptive control
Approximation
Artificial Intelligence
Closed loops
Computational Intelligence
Controllers
Design
Engineering
Fluid mechanics
Fuzzy control
Fuzzy logic
Management Science
Neural networks
Nonlinearity
Operations Research
Surface vehicles
Systems stability
Tracking control
Tracking errors
Tracking systems
Trajectory control
Uncertainty
Unmanned vehicles
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Title Nussbaum-Based Adaptive Fuzzy Tracking Control of Unmanned Surface Vehicles with Fully Unknown Dynamics and Complex Input Nonlinearities
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