Global Robust Adaptive Trajectory Tracking Control for Surface Ships Under Input Saturation

Zhu, Guibing

doi:10.1109/joe.2018.2877895

Cited by 105 publications

(39 citation statements)

References 33 publications

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“…Meanwhile, the time-varying ocean disturbances are chosen as In addition, in order to further verify the superiority of the proposed controller, MIAC index [27] is hired to quantify the tracking errors j e (j = x, y), which can be expressed as…”

Section: Initial Condition Controller Parametersmentioning

confidence: 99%

“…In the presence of the input saturation, an adaptive impedance controller is developed for an n-link robotic manipulator in [26], where an auxiliary system is adopted to handle the input saturation. The paper [27] designs a novel robust adaptive ship trajectory tracking control law for surface ships, in which the input saturation is approximated using a Gaussian error function. Hence, the influence of input saturation should be considered in control design.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Sliding Mode Trajectory Tracking Control for Unmanned Surface Vehicle with Modeling Uncertainties and Input Saturation

et al. 2019

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In the presence of modeling uncertainties and input saturation, this paper proposes a practical adaptive sliding mode control scheme for an underactuated unmanned surface vehicle (USV) using neural network, auxiliary dynamic system, sliding mode control and backstepping technique. First, the radial basis function neural network with minimum learning parameter method (MLP) is constructed to online approximate the uncertain system dynamics, which uses single parameter instead of all weights online learning, leading to a reduction in the computational burdens. Then a hyperbolic tangent function is adopted to reduce the chattering phenomenon due to the sliding mode surface. Meanwhile, the auxiliary dynamic system and the adaptive technology are employed to handle input saturation and unknown disturbances, respectively. In addition, a neural shunting model is introduced to eliminate the “explosion of complexity” problem caused by the backstepping method for virtual control derivation. The stability of the closed-loop system is guaranteed by the Lyapunov stability theory. Finally, simulations are provided to validate the effectiveness of the proposed control scheme.

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Section: Initial Condition Controller Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Trajectory Tracking Control for Unmanned Surface Vehicle with Modeling Uncertainties and Input Saturation

et al. 2019

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“…To verify the robustness of these comparative control algorithms, the complex modeling uncertainties d m can be simulated as: In addition, MIAC index [41] is introduced to evaluate and compare the tracking performance of these comparative control algorithms with the integrate consideration of the transient and steady-state tracking, which is designed as:…”

Section: Simulation a Simulation Setupmentioning

confidence: 99%

Adaptive Sliding Mode Control Design for Nonlinear Unmanned Surface Vessel Using RBFNN and Disturbance-Observer

et al. 2020

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Unmanned surface vessel(USV) has been applied in the maritime security inspection and resources exploration to execute complex works with its advantages in automation and intelligence. While the nonlinear USV working in the complex ocean environment, the good trajectory tracking performance is an important capacity. However, the nonlinearity, modeling uncertainties (e.g., modeling error and parameter variations) and external disturbance (wind, wave, current, etc) are the main difficulties, which deteriorates the control performance. To solve this issue, most existing algorithms for USV's tracking have been developed based on the linearization of the USV's nonlinear dynamic model at specific equilibrium point. However, the integrated effect of nonlinearities, modeling uncertainties and external disturbance has not been well considered, which can degrade the USV's tracking performance. Therefore, to achieve the good tracking performance for USV, a nonlinear dynamic model is strictly derived in this paper with the integrate consideration of abovementioned issues, and an adaptive sliding mode control design using RBFNN(Radial Basis Function Neural Network) and disturbance-observer is subsequently developed, where a RBFNN approximator is designed to approximate and compensate modeling uncertainties, and a disturbance-observer is designed to estimate and compensate the effect of the external disturbance. Furthermore, the global stability of the overall closed-loop system of USV are strictly guaranteed. The comparative simulation is carried out to validate the fast response, better transient performance and robustness of our proposed control design via comparing with the existing methods. INDEX TERMS Adaptive sliding mode control, neural network, unmanned surface vessel(USV), Lyapunov stability theorem, disturbance observer.

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“…It is well known that Euler-Lagrange systems (ELSs) can describe the motion behaviors of a wide number of physical systems, including robotic manipulators [1]- [2], aircrafts [3], surface ships [4], underwater vehicles [5], etc. In parctice, the uncertainties are frequently encountered in the operations of ELSs due to unmodeled nonlinearities, unknown parameters and external disturbances, which make the tracking control problem challenging.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Finite-Time Tracking Control for Uncertain Euler-Lagrange Systems With Input Saturation

et al. 2020

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In this paper, a robust adaptive finite-time (FT) tracking control scheme is proposed for Euler-Lagrange systems (ELSs) subject to nonparametric uncertainties, unknown disturbances and input saturation. In the design procedure, a Gaussian error function is utilized to approximate the input saturation nonlinearity. Following that, by employing the natural property that the upper bound of model parameters uncertainties is linear-in-parameters, the lumped uncertain term that caused by uncertain model parameters and external disturbances is formulated by a linear-parametric form with a single parameter. And then, a novel robust adaptive tracking control law is designed to resolve the tracking control problem of uncertain ELSs. The proposed control scheme is featured by FT convergence rate, and robustness against uncertainties and unknown disturbances. Furthermore, the robust adaptive FT tracking control scheme is insensitive to the character of the uncertainties, and is with low computational burden and easy to implement in engineering applications. And its rigorous stability is analyzed with the aid of the Lyapunov stability theory, and its effectiveness is verified by simulation results and comparison.

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Global Robust Adaptive Trajectory Tracking Control for Surface Ships Under Input Saturation

Cited by 105 publications

References 33 publications

Adaptive Sliding Mode Trajectory Tracking Control for Unmanned Surface Vehicle with Modeling Uncertainties and Input Saturation

Adaptive Sliding Mode Trajectory Tracking Control for Unmanned Surface Vehicle with Modeling Uncertainties and Input Saturation

Adaptive Sliding Mode Control Design for Nonlinear Unmanned Surface Vessel Using RBFNN and Disturbance-Observer

Robust Adaptive Finite-Time Tracking Control for Uncertain Euler-Lagrange Systems With Input Saturation

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