Path following control for marine surface vessel with uncertainties and input saturation

Zheng, Zewei; Sun, Liang

doi:10.1016/j.neucom.2015.11.017

Cited by 183 publications

(116 citation statements)

References 40 publications

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“…Accordingly, the closed‐loop system is proved to be ultimately uniformly bounded and the tracking error signals

ν_{e} = {([],,,,, x_{e}, y_{e}, \overset{true˜}{ψ}, \overset{true˜}{r}, {\overset{u}{true}}_{r})}^{T}

converge to an arbitrarily small neighborhood of zero.Remark For the lack of sway actuation, the sway velocity v r is left for free, which has been proved to be ultimately uniformly bounded in .…”

Section: Control Designmentioning

confidence: 99%

“…Proof: Assign the following complete Lyapunov function V = V 1 + V 2 + V 3 + V 4 , taking time derivative of it combining (22), (26), (37), and (44) yields:…”

Section: Stability Analysis Of Close-loop Systemmentioning

confidence: 99%

“…Remark 5. For the lack of sway actuation, the sway velocity v r is left for free, which has been proved to be ultimately uniformly bounded in [22].…”

Section: Stability Analysis Of Close-loop Systemmentioning

confidence: 99%

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Robust adaptive maneuvering control for an unmanned surface vessel with uncertainties

Huang

Fan

2019

IEEJ Transactions Elec Engng

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This article investigates the path‐following control problem of an unmanned surface vessel in the presence of uncertainties with only two inputs available (surge force and yaw moment). The problem consists of steering a vessel to follow a scheduled path with the desired velocity assignment. The backstepping technique and Lyapunov's direct method are employed as the main framework to design a controller. To ensure the design requirements, an improved integral line‐of‐sight guidance law is utilized first to calculate the desired yaw angle and to make compensation for the ocean currents based on the reduced‐order linear extended state observer. Then, a controller based on the radial basis function neural network is used to accomplish the yaw angle and velocity tracking, which alleviates the effects of model uncertainties and external disturbances. All the tracking error signals of the closed‐loop system are proved to be uniformly ultimately bounded. It demonstrates that the proposed path‐following control approach can deal well with time‐varying ocean currents, model uncertainties, and time‐varying disturbances. Results of the simulations validate the effectiveness and robustness of the proposed approach. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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“…Accordingly, the closed‐loop system is proved to be ultimately uniformly bounded and the tracking error signals

ν_{e} = {([],,,,, x_{e}, y_{e}, \overset{true˜}{ψ}, \overset{true˜}{r}, {\overset{u}{true}}_{r})}^{T}

Section: Control Designmentioning

confidence: 99%

“…Proof: Assign the following complete Lyapunov function V = V 1 + V 2 + V 3 + V 4 , taking time derivative of it combining (22), (26), (37), and (44) yields:…”

Section: Stability Analysis Of Close-loop Systemmentioning

confidence: 99%

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Robust adaptive maneuvering control for an unmanned surface vessel with uncertainties

Huang

Fan

2019

IEEJ Transactions Elec Engng

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“…An adaptive fuzzy robust algorithm 19 has been developed for the tracking control design of a vehicle autopilot system with the uncertain system function, the uncertain gain function, and the unknown nonlinear functions that are caused by modeling errors and external disturbances. [21][22][23][24] In order to consider uncertain vehicle dynamics and input constraints at the same time, Kahveci and Ioannou 21 proposed an adaptive steering control design based on the antiwindup technique. 20 Hence, the control input is often constrained, and the controllability of the system is severely influenced.…”

Section: Introductionmentioning

confidence: 99%

Robust adaptive steering control for unmanned surface vehicle with unknown control direction and input saturation

Wang

2019

Adaptive Control & Signal

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A robust adaptive steering control method is proposed to solve the control problem of the unmanned surface vehicle (USV) with uncertainties, unknown control direction, and input saturation. In the controller design process, the adaptive fuzzy system is incorporated into dynamic surface control (DSC) to approximate the uncertainty term induced by external environmental disturbances and model parameters. Then, the Nussbaum function is used to eliminate the requirement for a priori knowledge of the control direction. Besides, to handle the input saturation, the adaptive fuzzy DSC is extended by a second-order nonlinear filter and antisaturation auxiliary function to compensate for the magnitude and rate saturation of the rudder. All signals of the closed-loop system are proven to be uniformly ultimately bounded (UUB) by Lyapunov theorem and the Lemma of Nussbaum gain, and the course error can converge to a small neighborhood of zero through choosing design parameters appropriately. Finally, simulation results and comprehensive comparisons are shown for the USV course system, which is demonstrative of the proposed controller's effectiveness and robustness. KEYWORDSdynamic surface control, input saturation, robust adaptive, unknown control direction, USV steering system 1212

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“…Tracking geometric paths in output spaces of nonlinear systems subject to input and state constraints without pre-specified timing requirements, commonly referred to as the constrained output path following problem, is considered in [19], where a predictive control approach is proposed to constrained path following problems with and without velocity assignments. The path following control problem for an unmanned marine surface vessel in the presence of uncertainties and input saturation is presented in [20], where the backstepping technique, augmented by a robust adaptive radial basis function neural network (RBFNN) and an auxiliary design system, is employed as the main control framework. A two-dimensional path following control system for autonomous surface vehicles is presented in [21], where the guidance system is obtained through a waypoint guidance scheme based on a vector field algorithm.…”

Section: Introductionmentioning

confidence: 99%

Path Following Control of the Underactuated USV Based On the Improved Line-of-Sight Guidance Algorithm

Liu¹,

Dong

Hong-wang³

et al. 2017

Polish Maritime Research

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Path following control for marine surface vessel with uncertainties and input saturation

Cited by 183 publications

References 40 publications

Robust adaptive maneuvering control for an unmanned surface vessel with uncertainties

Robust adaptive maneuvering control for an unmanned surface vessel with uncertainties

Robust adaptive steering control for unmanned surface vehicle with unknown control direction and input saturation

Path Following Control of the Underactuated USV Based On the Improved Line-of-Sight Guidance Algorithm

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