Disturbance-Observer-Based Sliding Mode Control Design for Nonlinear Unmanned Surface Vessel With Uncertainties

Chen, Zheng; Zhang, Yougong; Zhang, Youming; Nie, Yong; Tang, Jianzhong; Zhu, Shiqiang

doi:10.1109/access.2019.2941364

Cited by 29 publications

(14 citation statements)

References 37 publications

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“…Using Simulink in MATLAB, the actual solved six-degreeof-freedom robot manipulator model obtained in this section is simulated and verified. And the control algorithm in the literature [42] is applied to this system, and then the comparison test of the two algorithms is realized. The inherent parameters of the system are as follow: The control algorithm in the literature [42] is used for trajectory tracking and velocity tracking of the system, and the simulation results of joints 1 and 2 are presented.…”

Section: Analysis Of Simulation Resultsmentioning

confidence: 99%

“…And the control algorithm in the literature [42] is applied to this system, and then the comparison test of the two algorithms is realized. The inherent parameters of the system are as follow: The control algorithm in the literature [42] is used for trajectory tracking and velocity tracking of the system, and the simulation results of joints 1 and 2 are presented. Using the control algorithm designed in this paper, the simulation results obtained are shown in Figure 3-figure 6.…”

Section: Analysis Of Simulation Resultsmentioning

confidence: 99%

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P-Rob Six-Degree-of-Freedom Robot Manipulator Dynamics Modeling and Anti-Disturbance Control

Zhang¹,

2021

IEEE Access

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In this paper, the problem of modeling and anti-disturbance control is studied for lightweight personal robotics (P-Robs) with a six-degree-of-freedom robot manipulator to solve the movement instability phenomenon caused by time-varying uncertain disturbances during the movement of the robot manipulator. The detailed dynamical equations of the P-Rob system are solved based on the Lagrange energy equation, and the actual dynamical model of the robot manipulator system is obtained. The disturbance observer is designed to estimate the disturbance effectively, and an integral sliding mode control algorithm is proposed to realize tracking control. Stability analysis of the system is carried out using the Lyapunov function. Finally, experiments are conducted on an actual P-Rob system model, and the experimental results show that the robot manipulator system tracks the desired trajectory effectively, which validates the effectiveness of the proposed control algorithm.INDEX TERMS P-Rob system, robot manipulator, dynamical modeling, disturbance observer, integral sliding mode control, track tracking.

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Section: Analysis Of Simulation Resultsmentioning

confidence: 99%

Section: Analysis Of Simulation Resultsmentioning

confidence: 99%

P-Rob Six-Degree-of-Freedom Robot Manipulator Dynamics Modeling and Anti-Disturbance Control

Zhang¹,

2021

IEEE Access

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“…where β represents the sideslip angle which can be calculated by β=atan2 v u . With the abovementioned surge dynamics (14), yaw dynamics (23), and sway dynamics (16), the linearized dynamic model of USV is summarized as: where x = u β ψ r T represents the motion state of USV, δ= T δ r T represents the control input,…”

Section: B Linear Modelingmentioning

confidence: 99%

“…C3: Sliding mode controller proposed in [16]. The primary parameters are specified as K v = diag{100, 100, 100}, ξ = diag{100, 100, 100}, K = diag{10, 10, 10}, H = diag{0.1309, 0.1309, 0.1309}, δ = 0.1, = 0.1.…”

Section: Simulation a Simulation Setupmentioning

confidence: 99%

“…For the USV's trajectory tracking with complex external disturbances, some trajectory control algorithms have been proposed based on nonlinear dynamic model [16]- [23], such as adaptive back-stepping control, sliding mode control, neural network-based control, model predictive control, etc. For instance, to achieve the good tracking performance, a disturbance-observer-based sliding mode control design is proposed in [16], where a disturbance observer is designed to estimate and compensate the modeling uncertainties and external disturbance. A nonlinear modeling scheme based on active Kalman filter was proposed by Han et al [24] to estimate and compensate the unstructured model.…”

Section: Introductionmentioning

confidence: 99%

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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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Robust neural network‐based tracking control for unmanned surface vessels under deferred asymmetric constraints

Sun

Qin

et al. 2021

Intl J Robust & Nonlinear

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In this article, the constraints on unmanned surface vessels are imposed after a certain time after the system operation. Based on the shift function, this article proposes an asymmetric barrier Lyapunov function and achieves the control scheme with deferred and asymmetric full-state constraints. In addition, radial basis function neural network and an antiwindup compensator are adopted for the problems of uncertainties and input saturation. The simulation results demonstrate the feasibility of the proposed control strategies.

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Disturbance-Observer-Based Sliding Mode Control Design for Nonlinear Unmanned Surface Vessel With Uncertainties

Cited by 29 publications

References 37 publications

P-Rob Six-Degree-of-Freedom Robot Manipulator Dynamics Modeling and Anti-Disturbance Control

P-Rob Six-Degree-of-Freedom Robot Manipulator Dynamics Modeling and Anti-Disturbance Control

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

Robust neural network‐based tracking control for unmanned surface vessels under deferred asymmetric constraints

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