Two-Step Adaptive Control for Planar Type Docking of Autonomous Underwater Vehicle

Wang, Tianlei; Sun, Zhenxing; Ke, Yun; Li, Chaochao; Hu, Jiwei

doi:10.3390/math11163467

Cited by 6 publications

(3 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Zhang developed a model-free docking controller using deep reinforcement learning to complete threedimensional docking tasks under disturbances [8]. Wang proposed a two-step adaptive control method to solve the planar-type docking problem, seamlessly combining horizontal dynamic positioning and visual servo docking [9].…”

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

View full text Add to dashboard Cite

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.

show abstract

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

View full text Add to dashboard Cite

show abstract

“…Nevertheless, the control signal of MPC is an implicit function, presenting a challenge to the closed-loop stability of the system [11,12]. Compared with these control methods, adaptive control has been a meaningful subject for nonlinear systems which is suitable for the trajectory tracking control of underactuated AUVs [13,14]. In particular, backstepping-based adaptive control has become one of the common methods to solve problems of nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Observer-Based Adaptive Control for Trajectory Tracking of AUVs with Input Saturation

Li,

Lv,

Lai

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

In this paper, an observer-based adaptive control method is investigated for the horizontal trajectory tracking of autonomous underwater vehicles (AUV) with input saturation and system disturbances. Firstly, the desired surge speed and trajectory angle are established, which could decouple the tracking error subsystem and avoid the complex form. Secondly, the input saturation is approximated by a smooth function, and a nonlinear extended states observer (NESO) is designed for estimating system disturbances. Based on the command filtered backstepping technique, which can avoid the explosion caused by the derivative of the virtual control, an observer-based adaptive output feedback control method is developed, and an auxiliary system is applied to compensate for filtered tracking errors, input saturation bias, and observer errors. Finally, simulation results show the proposed method has good robustness in the face of system uncertainties, and the error is nearly 33.3% smaller than that of other control methods when meeting sudden trajectory changes. A good control performance is guaranteed.

show abstract

“…For linear systems without uncertainty in the plant model parameters, the classical control methods, such as modal control, optimal control, etc., refs. [11][12][13][14][15] can ensure that the control error between the controlled signal and reference signal converges to an arbitrarily small region after a finite time. The characteristics of the transient process can be easily obtained by analyzing the dynamic model via a transfer function or state-space model.…”

Section: Introductionmentioning

confidence: 99%

Output Stabilization of Linear Systems in Given Set

Nguyen

Furtat

2023

Mathematics

View full text Add to dashboard Cite

This paper presents a method for designing control laws to achieve output stabilization of linear systems within specified sets, even in the presence of unknown bounded disturbances. The approach consists of two stages. In the first stage, a coordinate transformation is utilized to convert the original system with output constraints into a new system without constraints. In the second stage, a controller is designed to ensure the boundedness of the controlled variable of the transformed system obtained in the first stage. Two distinct control strategies are presented in the second stage, depending on the measurability of the state vector. If the state vector is measurable, a controller is designed using state feedback based on the Lyapunov method and Linear Matrix Inequalities (LMIs). Alternatively, if only the output vector is measurable, an observer-based controller is designed using a Luenberger observer. In this case, the state estimation error does not need to converge to zero but must remain bounded. The efficacy of the proposed method and the validity of the theoretical results are demonstrated through simulations performed in MATLAB/Simulink.

show abstract

Two-Step Adaptive Control for Planar Type Docking of Autonomous Underwater Vehicle

Cited by 6 publications

References 33 publications

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

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

Observer-Based Adaptive Control for Trajectory Tracking of AUVs with Input Saturation

Output Stabilization of Linear Systems in Given Set

Contact Info

Product

Resources

About