Adaptive control for fully-actuated autonomous surface vehicle with uncertain model and unknown ocean currents

Souissi, Sami; Boukattaya, Mohamed; Damak, Tarak; Nejim, Samir

doi:10.1016/j.oceaneng.2020.108147

Cited by 19 publications

(3 citation statements)

References 42 publications

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“…Consequently, it is concluded that the virtual velocity command Equation (12), designed by the outer-loop kinematic control, is also bounded. According to the Barbalat Lemma [31], .…”

Section: Kinematic Controlmentioning

confidence: 99%

Dynamic Modeling and Robust Trajectory Tracking Control of a Hybrid Propulsion-Based Small Underwater Robot

Wang,

et al. 2023

JMSE

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This paper proposes a hybrid propulsion-based small underwater robot for robust trajectory tracking control in a harsh and complex underwater environment. The robot is equipped with a Coanda-effect jet thruster and a pair of propeller-based reconfigurable magnetic-coupling thrusters, allowing it to traverse safely in confined or cluttered spaces as well as cruise efficiently in the open water. To investigate the robot dynamic modeling, we first formulated its simplified mathematical model and estimated the hydrodynamic coefficients by performing the planar motion mechanism using CFD (computational fluid dynamics) simulation. Then, a double-loop trajectory tracking control architecture was designed considering the model uncertainties and environmental disturbances. Based on Lyapunov theory, the outer-loop kinematic control produces the virtual velocity command, while the inner-loop dynamic control adopts the full-state feedback L1-adaptive control to match the command. The asymptotic convergence of the tracking errors and the stability of the whole closed-loop system are guaranteed. Finally, comparative simulations in the presence of unknown disturbances and the variation of model parameters were carried out to verify the robustness of our proposed trajectory tracking control, which is also suitable for the separated son robots.

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“…Consequently, it is concluded that the virtual velocity command Equation (12), designed by the outer-loop kinematic control, is also bounded. According to the Barbalat Lemma [31], .…”

Section: Kinematic Controlmentioning

confidence: 99%

Dynamic Modeling and Robust Trajectory Tracking Control of a Hybrid Propulsion-Based Small Underwater Robot

Wang,

et al. 2023

JMSE

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“…In order to have better adaptability and high precision underwater tracking of ROV system, a feedforward controller based on neural network was proposed to compensate for hysteresis of PID. The neural network has high fault tolerance, strong self‐learning, self‐organizing and self‐adaptive ability, which can simulate complex nonlinear mapping and improve tracking accuracy and stability (Souissi et al, 2020). Besides, it can not only give full play to the advantages of feedforward control, but also maintain the robustness of feedback control (Ma et al, 2020).…”

Section: The Hybrid Control Strategymentioning

confidence: 99%

Intelligent control method of underwater inspection robot in netcage

Liu

Wei

et al. 2021

Aquaculture Research

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The traditional netcage inspection requires divers to complete, which is inefficient and dangerous. The underwater robot inspection is a way to solve the problem. When the robot is in motion, the camera shoots the netcage, replacing the manual inspection. A new hybrid control strategy based on neural network (NN) and proportional integral differential (PID) is proposed for underwater three‐dimensional path tracking, which overcomes the defect that the traditional feedback regulation can only work after the occurrence of deviation. A feedforward controller based on neural network is designed to predict the disturbance of the controlled object and enhance the anti‐interference ability of the system. Firstly, implement global path tracking based on azimuth and course. Then when the remotely operated vehicle (ROV) deviates from the path, local path planning with rapidly‐exploring random trees (RRT) algorithm. ROV tracks local path and returns to the global path. Finally, using the moving average (MA) algorithm of RRT path smoothing, a smooth path is obtained to minimize ROV jitter, which ensures that the ROV can clearly take pictures of the netcage, and the service life of the ROV is extended. ROV can replace manual inspection, and it only takes about 30 min to rotate a circle, greatly improving work efficiency. The control approach was tested underwater at different depth path tracking scenarios. The experimental results show that in the case of waves <0.5 m, the average tracking error of ROV is <0.5 m, the fluctuation of roll angle and pitch angle is <6°, the average distance error from ROV to mesh netcage is about 0.2 m, and the underwater netcage inspection task is completed stably. [Video attachment: https://youtu.be/NKcgPcej5sI].

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“…In [4], in order to realize ship trajectory tracking, an event-triggered trajectory tracking control method for fullyactuated surface warship based on guidance control structure was proposed. In [5], authors proposed a robust adaptive controller for the trajectory tracking of an autonomous surface vehicle (ASV) in the presence of model uncertainties, ocean currents, and time-varying environmental disturbances.…”

Section: Introductionmentioning

confidence: 99%

Adaptive on-Line Approximator-Based Finite-Time Trajectory Tracking Control for the Surface Vessel

et al. 2022

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An adaptive finite-time trajectory tracking scheme is proposed to solve the problem of trajectory tracking of underactuated surface ship affected by dynamic uncertainties and external disturbances. In this scheme, underactuated transformation is performed by using kinematic virtual control law transformation and bounded constraint. By designing adaptive control to approach the upper bound of uncertainty and unknown disturbance, the problem of parameter uncertainty and external disturbance are solved. It is proven by Lyapunov theory that the error signals in the system can converge quickly to the stable region in finite time. Finally, by comparing the simulation results, it is verified that the proposed control scheme can make the underactuated ship track the desired trajectory in finite time. Compared to the traditional control method, the convergence rate of the system error is faster, and it exhibits strong robustness in the face of unknown external disturbances. This has a certain reference value for practical engineering applications.

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Adaptive control for fully-actuated autonomous surface vehicle with uncertain model and unknown ocean currents

Cited by 19 publications

References 42 publications

Dynamic Modeling and Robust Trajectory Tracking Control of a Hybrid Propulsion-Based Small Underwater Robot

Dynamic Modeling and Robust Trajectory Tracking Control of a Hybrid Propulsion-Based Small Underwater Robot

Intelligent control method of underwater inspection robot in netcage

Adaptive on-Line Approximator-Based Finite-Time Trajectory Tracking Control for the Surface Vessel

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