Heading Control of USV by Expert-Fuzzy Technology

Dong, Zaopeng; Wan, Liu; Li, Yueming; Liao, Yu-Lei; Zhuang, Jiayuan

doi:10.14257/ijca.2015.8.12.14

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…For the appropriate method of the trajectory tracking, it is a prerequisite that the control methodology of the trajectory tracking, either with deterministic model parameters or with uncertain model parameters, are known as precisely as possible. Moreover, the trajectory tracking methods of the control system usually include five types (line-of-sight (LOS) guidance algorithm [ 11 ], adaptive proportional-integral-differential (PID) algorithm [ 12 ], fuzzy control method [ 13 ], sliding mode control method [ 14 ], neural network control method [ 15 ]) during the regulating of control parameters. These methods could significantly improve control performance.…”

Section: Introductionmentioning

confidence: 99%

A trajectory tracking control system for paddle boat in intelligent aquaculture

Guo,

Zhang,

Zeng

et al. 2023

PLoS ONE

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Trajectory tracking plays a notable role in unmanned surface vehicles (USV), especially for the emerging intelligent aquaculture, as the level of integration, high-efficiency, and low-labor-intensity of such USV is determined by trajectory tracking. Here, we report a generic trajectory tracking control system for a paddle boat by establishing a three-degree-of-freedom kinematics model, which could precisely characterize the relationship between velocities, forces and moments of the paddle boat. A Pixhawk 4 as the core controller of the hardware system could be integrated with the other hardware submodules and could complete the wireless data transmission, monitoring and remote control functions. Meanwhile, we establish a fuzzy rule table, consider the advantages of line-of-sight (LOS) guidance and fuzzy adaptive proportional-integral-differential (PID) algorithm, combine the two parts and apply them as the key algorithm in the trajectory tracking of the paddle boat. Demonstrations include trajectory tracking effect at different velocities, turning effect at left-turn moment, and trajectory tracking effect at different turning angles. The results show that the paddle boat is able to travel under the trajectory formed by following the planned waypoints within the error allowed, which is called effective trajectory tracking. And can offer an alternative pathway toward achieving effective trajectory tracking control in advanced intelligent aquaculture USV for smartly and wirelessly operated pond drug spraying.

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Section: Introductionmentioning

confidence: 99%

A trajectory tracking control system for paddle boat in intelligent aquaculture

Guo,

Zhang,

Zeng

et al. 2023

PLoS ONE

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Dynamic modelling and controlling Unmanned Surface Vehicle

Setiawan

Kadir

Gamayanti

et al. 2021

IOP Conf. Ser.: Earth Environ. Sci.

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Unmanned Surface Vehicle (USV) is vessel that can move without human to control. USV is capable of moving using the thrust force and can maneuver using the deflection angle of rudder. USV has a 6-degree of freedom which are non-linear system that can be approached with the 3-degrees of freedom. The purpose of dynamic modeling of USV is to achieve the models and parameters of real USV. Non-linear least square Levenberg-Marquardt method can be applied to estimate USV model as a non-linear system. The purpose of controlling USV is to set the surge velocity and the yaw-rate so that the USV movement can be controlled. Proportional integral controller can be used to manipulate the velocity and to accelerate the response speed of the USV’s velocity. Parameters validation results show that the dynamic modeling methods could generate the parameters nearly equal to the true parameters. This is evidenced by the relatively small RMSE value in x-axis acceleration, y-axis acceleration, and yaw-axis acceleration. The result of controller testing illustrate that the designed controller can adjust the surge velocity and yaw-rate and fit the time constant controller design specification. Further, the testing show that the responses have zero steady state errors.

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