Robust Adaptive Tracking Control of the Underwater Robot with Input Nonlinearity Using Neural Networks

Chen, Mou; Jiang, Bin; Zou, Jie; Feng, Xiao

doi:10.1080/18756891.2010.9727730

Cited by 30 publications

(16 citation statements)

References 23 publications

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“…Therefore, the conditions in Theorem 3 must be satisfied. Based on the LP method, we obtain the control gain matrices F and K as follows: According to (54), the eigenvalues of Q are given as λ 1 (Q) = −2.9262, λ 2 (Q) = −2.8207, λ 3 (Q) = −1.0276 and λ 4 (Q) = −1.6309. Therefore, the eigenvalues of Q locate in the left half complex plane.…”

Section: E Simulation Of a Fractional Electrical Circuitmentioning

confidence: 99%

“…The disturbance observer based control schemes were proposed for near-space vehicles (NSV) in [52], [53]. In [54], a robust adaptive tracking control scheme was proposed for the underwater robot in the presence of parametric uncertainties and unknown external disturbances. The robust attitude control scheme was developed for NSV with time-varying disturbances based on backstepping technique in [55].…”

Section: Introductionmentioning

confidence: 99%

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Stabilization Control of Continuous-Time Fractional Positive Systems Based on Disturbance Observer

Shao

2016

IEEE Access

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This paper studies the problem of stabilization control for a class of continuous-time fractional systems subject to external constant disturbances based on a disturbance observer. To tackle unknown disturbances, a fractional disturbance observer (FDO) is introduced for the fractional system. A stabilization controller incorporating the disturbance observer is then designed for the fractional system. Under the developed control scheme and linear program (LP) method, the sufficient conditions are proposed to guarantee that the fractional systems with closed-loop positivity are asymptotically stable. Numerical simulation results further demonstrate the effectiveness of the results.

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Section: E Simulation Of a Fractional Electrical Circuitmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stabilization Control of Continuous-Time Fractional Positive Systems Based on Disturbance Observer

Shao

2016

IEEE Access

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“…The initial intervehicle distances in all the tests are 32 m. Two different overtaking control methods have been compared in the same scenes. One is the proposed conflict-probability-estimation-based overtaking control method; the other method has been described in 9 .…”

Section: Overtaking Simulation Examplementioning

confidence: 99%

“…How to keep them with constant position and how to reduce position and velocity error is the main problem of this issue. Some research uses adaptive tracking control method for solving these problems 9 .…”

Section: Platoon Simulation Examplementioning

confidence: 99%

CyberTORCS: An Intelligent Vehicles Simulation Platform for Cooperative Driving

Yang¹,

Wan²,

Wang³

et al. 2011

IJCIS

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Simulation platforms play an important role in helping intelligent vehicle research, especially for the research of cooperative driving due to the high cost and risk of the real experiments. In order to ease and bring more convenience for cooperative driving tests, we introduce an intelligent vehicle simulation platform, called CyberTORCS, for the research in cooperative driving. Details of the simulator modules including vehicle body control, vehicle visualization modeling and track visualization modeling are presented. Two simulation examples are given to validate the feasibility and effectiveness of the proposed simulation platform.

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“…Most researchers utilized GPS, ultrasonic [1][2][3] , optical flow sensor or machine vision based systems to provide the positioning information. The precision or reliability of results can be improved with several sensors [4][5][6][7] . However, the problems associated with using GPS for vehicle navigation are insufficient position accuracy and signal blockage due to buildings and hilly terrain.…”

Section: Introductionmentioning

confidence: 99%

Improved Intelligent Vehicle Localization Using Magnetic Ruler

Wang¹,

Yang²,

Wang³

et al. 2011

IJCIS

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This paper proposes an improved intelligent vehicle localization method, which integrates the data from the odometry and the magnetic ruler(MR). The MR is used to detect the magnetic markers, which provides the absolute positioning reference. The data from odometry and the MR are used to localize the vehicle by using unscented Kalman filter. The data association (DA) method is adopted to validate the observations from the MR. The experiment results show that the method is a robust way.

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Robust Adaptive Tracking Control of the Underwater Robot with Input Nonlinearity Using Neural Networks

Cited by 30 publications

References 23 publications

Stabilization Control of Continuous-Time Fractional Positive Systems Based on Disturbance Observer

Stabilization Control of Continuous-Time Fractional Positive Systems Based on Disturbance Observer

CyberTORCS: An Intelligent Vehicles Simulation Platform for Cooperative Driving

Improved Intelligent Vehicle Localization Using Magnetic Ruler

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