A practical robust yaw servo architecture of ROVs by multi-vector propulsion and nonlinear controller

Song, Dalei; Li, Lin; Wang, Changbin; Hou, Renyu; Liu, Chong

doi:10.1177/0142331220932373

Cited by 4 publications

(4 citation statements)

References 28 publications

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“…Currently, most unmanned underwater platforms' attitude control can't cope with changing motion models generated by carrying different devices, and most attitude control algorithms are limited to the simulation level [22,23]. In contrast, the more mature traditional PID control has low accuracy and can't meet the application requirements under high interference [24]. To solve the motion and attitude control problems of the unmanned underwater platform, this paper proposes a model-referenced adaptive PID control algorithm.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: Research on motion and attitude control of unmanned underwater platform

Jin,

Miao,

Cui

2023

Preprint

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Unmanned underwater platforms are commonly used in ocean exploration and development to help researchers understand underwater conditions. A Model Reference Adaptive PID (MRAC-PID) control method is designed to solve the problem that a small unmanned underwater platform can’t carry different equipment to maintain motion and attitude stability in the harsh seabed environment. In this paper, the kinematic and dynamic system model of the platform in the stable state is set as the reference model of the control algorithm. When the model parameters of the controlled object change due to the environment or its factors, the controller will compare the control difference between the reference model and the controlled object. At the same time, the tracking control error will be fed back to the adaptive adjusting mechanism in real-time, so that the controller keeps iterating the control parameters. Through continuous optimization of control parameters, the control effect of the controlled object and the reference model can be kept consistent at all times so that the attitude of the unmanned underwater platform can be kept stable at all times. Compared with the traditional PID and fuzzy PID control algorithm, the algorithm developed in this paper improved the control performance indicators greatly. Even though the system model structure and parameters change with the operating environment, the MRAC-PID control algorithm is still effective and shows a very good robustness. The proposed control approach is also suitable for real-time application, which can provide a reference for the subsequent related researches.

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Section: Introductionmentioning

confidence: 99%

RETRACTED: Research on motion and attitude control of unmanned underwater platform

Jin,

Miao,

Cui

2023

Preprint

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“…Wu proposed a hybrid proportional integral derivative (PID) controller for a work-class ROV to achieve high-performance maneuvering [5]. Song developed an improved model-based PI robust controller using a nominal model for the precise positioning control of a hexagonal multi-vector propulsion ROV with communication time-delay constraints [6]. Li utilized a linear ADRC scheme that combines a reduced-order extended state observer and approximate time-optimal control; simulation results confirmed its effective control performance [7].…”

Section: Introductionmentioning

confidence: 99%

Fractional Active Disturbance Rejection Positioning and Docking Control of Remotely Operated Vehicles: Analysis and Experimental Validation

Liu,

Guo,

et al. 2024

Fractal Fract

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In this paper, a fractional active disturbance rejection control (FADRC) scheme is proposed for remotely operated vehicles (ROVs) to enhance high-precision positioning and docking control in the presence of ocean current disturbances and model uncertainties. The scheme comprises a double closed-loop fractional-order PIλDμ controller (DFOPID) and a model-assisted finite-time sliding-mode extended state observer (MFSESO). Among them, DFOPID effectively compensates for non-matching disturbances, while its fractional-order term enhances the dynamic performance and steady-state accuracy of the system. MFSESO contributes to enhancing the estimation accuracy through the integration of sliding-mode technology and model information, ensuring the finite-time convergence of observation errors. Numerical simulations and pool experiments have shown that the proposed control scheme can effectively resist disturbances and successfully complete high-precision tasks in the absence of an accurate model. This underscores the independence of this control scheme on accurate model data of an operational ROV. Meanwhile, it also has the advantages of a simple structure and easy parameter tuning. The FADRC scheme presented in this paper holds practical significance and can serve as a valuable reference for applications involving ROVs.

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“…In the past decades, unmanned underwater vehicles (UUVs) have been used thoroughly in the oil and gas industry, and scientific communities (Allibert et al, 2019;Song et al, 2020;Xing et al, 2017). UUVs usually can be divided into two categories: the first category is remotely operated vehicles (ROVs) and the other category is autonomous underwater vehicles (AUVs).…”

Section: Introductionmentioning

confidence: 99%

Observer-based adaptive neural sliding mode trajectory tracking control for remotely operated vehicles with thruster constraints

Chu

Chen²,

Zhu

et al. 2021

Transactions of the Institute of Measurement and Control

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For a class of remotely operated vehicle (ROV) systems with thruster constraints, immeasurable states, and unknown nonlinearities, the trajectory tracking control problem was discussed in this paper. The unknown nonlinear functions were approximated by radial basis function (RBF) neural networks. An adaptive state observer based on neural networks was designed and the immeasurable states were estimated. Considering the problem of thruster saturation constraints, an auxiliary system for saturation compensation was designed and a saturation factor was constructed by the auxiliary system state. By applying the backstepping design method, an adaptive neural sliding mode trajectory tracking controller was developed, in which the saturation factor is contained in adaptive laws. It was proved that the uniformly ultimately bounded (UUB) of trajectory tracking errors can be obtained. Finally, the effectiveness of the proposed trajectory tracking control approach was checked by simulations.

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A practical robust yaw servo architecture of ROVs by multi-vector propulsion and nonlinear controller

Cited by 4 publications

References 28 publications

RETRACTED: Research on motion and attitude control of unmanned underwater platform

RETRACTED: Research on motion and attitude control of unmanned underwater platform

Fractional Active Disturbance Rejection Positioning and Docking Control of Remotely Operated Vehicles: Analysis and Experimental Validation

Observer-based adaptive neural sliding mode trajectory tracking control for remotely operated vehicles with thruster constraints

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