Adaptive output-feedback control with prescribed performance for trajectory tracking of underactuated surface vessels

Jia, Zehua; Hu, Zhihuan; Zhang, Guoqing

doi:10.1016/j.isatra.2019.04.035

Cited by 106 publications

(58 citation statements)

References 25 publications

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“…Nevertheless, the ever-increasing complexity of marine environment and automation pose a variety of challenges for tracking a controller design of USVs. To guarantee desirable tracking performances, researchers have put forward a great diversity of control algorithms for USVs, involving prescribed performance control [1][2][3], backstepping control [4][5][6], and sliding-mode control [7][8][9]. Specifically, sliding-mode control has become a current research hotspot due to its robustness to external disturbances, model uncertainties, and system parametric variations.…”

Section: Introductionmentioning

confidence: 99%

Integral Sliding Mode Based Finite-Time Tracking Control for Underactuated Surface Vessels with External Disturbances

Xiao

Yang

Liu

et al. 2021

JMSE

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This study focuses on the problem of finite-time tracking control for underactuated surface vessels (USVs) through sliding-mode control algorithms with external disturbances. Considering the nonexistence of relative degree caused by the underactuated property, the initial tracking error system is firstly transformed to a high order system for the possibility of applying a sliding-mode control algorithm. Subsequently, a finite-time controller based on an integral sliding surface (ISMS) is designed to achieve trajectory tracking. With the aid of this controller, the tracking errors converge to a steady state in a finite time. In contrast to the backstepping-based approach, the proposed method makes it possible to integrate controller design of position tracking and attitude tracking in one step, thus ensuring simplicity for implementation. Finally, theoretical analysis and numerical simulations are conducted to confirm the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Integral Sliding Mode Based Finite-Time Tracking Control for Underactuated Surface Vessels with External Disturbances

Xiao

Yang

Liu

et al. 2021

JMSE

View full text Add to dashboard Cite

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“…In practical applications, it is realistic and of great significance to consider that the USV position error should be limited strictly by both sides of the feasible channel to ensure the navigation safety of the vessel [6]. With this problem in mind, efforts have been made by researchers to satisfy the output constraint of the system, and there appears to be a variety of control schemes, such as the barrier Lyapunov function (BLF) [29][30][31][32], nonlinear mapping (NM) control [13,29], and prescribed performance (PP) control [30][31][32]. To restrain tracking error variables, the use of logarithmic BLF [33] and tantype BLF [34], in conjunction with an adaptive algorithm, was proposed for the trajectory control of single and multiple underactuated surface vessels, respectively.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Tracking Control for Underactuated USV with Prescribed Performance and Input Quantization

Jiang

Mao

et al. 2021

Symmetry

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This paper is devoted to the problem of prescribed performance trajectory tracking control for symmetrical underactuated unmanned surface vessels (USVs) in the presence of model uncertainties and input quantization. By combining backstepping filter mechanisms and adaptive algorithms, two robust control architectures are investigated for surge motion and yaw motion. To guarantee the prespecified performance requirements for position tracking control, the constrained error dynamics are transformed to unconstrained ones by virtue of a tangent-type nonlinear mapping function. On the other hand, the inaccurate model can be identified through radial basis neural networks (RBFNNs), where the minimum learning parameter (MLP) algorithm is employed with a low computational complexity. Furthermore, quantization errors can be effectively reduced even when the parameters of the quantizer remain unavailable to designers. Finally, the effectiveness of the proposed controllers is verified via theoretical analyses and numerical simulations.

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“…In [30], a state transformation method is developed to solve a coupled USV dynamic model. In [31], the aforementioned coordinate transformation method is used to investigate an adaptive output feedback controller for USV trajectory tracking. In [32], an adaptive USV trajectorytracking controller is combined with a high-gain observer and a predefined performance function based on a realistic dynamical model.…”

Section: Introductionmentioning

confidence: 99%

Robust Neural Network Trajectory-Tracking Control of Underactuated Surface Vehicles Considering Uncertainties and Unmeasurable Velocities

2021

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This article focuses on the trajectory-tracking of an underactuated surface vehicle (USV) considering model uncertainties and nonlinear environmental disturbances. For trajectory tracking in an actual USV sailing environment, both the inertia and damping matrixes are not diagonal, the velocities states are unmeasurable, and error constraints and input saturation are considered. A robust control strategy is proposed based on the backstepping method, state transformation, a super-twisting state observer, and neural networks. All the closed-loop signals are uniformly ultimately bounded, which is proved by the Lyapunov stability theory analysis. The advantages of the proposed method are as follows. (i) A super-twisting observer is constructed to solve the problem of the velocities being unmeasurable, and the error between the virtual and actual velocities converges to a small neighborhood around zero. (ii) Additional controllers are developed to address input saturation of the system control. (iii) A predefined function design is employed to guarantee the transient trajectory-tracking performance. Finally, simulation results verify the feasibility and effectiveness of the proposed USV trajectory-tracking control method.INDEX TERMS Underactuated surface vehicle, trajectory tracking, prescribed performance, neural network, output feedback control.

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Adaptive output-feedback control with prescribed performance for trajectory tracking of underactuated surface vessels

Cited by 106 publications

References 25 publications

Integral Sliding Mode Based Finite-Time Tracking Control for Underactuated Surface Vessels with External Disturbances

Integral Sliding Mode Based Finite-Time Tracking Control for Underactuated Surface Vessels with External Disturbances

Trajectory Tracking Control for Underactuated USV with Prescribed Performance and Input Quantization

Robust Neural Network Trajectory-Tracking Control of Underactuated Surface Vehicles Considering Uncertainties and Unmeasurable Velocities

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