Sliding mode adaptive control for ship path following with sideslip angle observer

Zhang, Hugan; Zhang, Xianku; Bu, Renxiang

doi:10.1016/j.oceaneng.2022.111106

Cited by 26 publications

(4 citation statements)

References 27 publications

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“…Given the susceptibility of UUVs to external disturbances during navigation, along with the possibility of perturbations in their inherent model parameters, which can substantially affect control effectiveness, a disturbance observer is carefully designed to precisely estimate external environmental disturbances [37,38].…”

Section: Design Of Disturbance Observermentioning

confidence: 99%

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Trajectory Tracking Control of Unmanned Underwater Vehicle Based on Projected Perpendicular Guidance Method with Disturbance Observer

Liu,

Zhang,

Zhang

2024

JMSE

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Unmanned underwater vehicles (UUVs) possess impressive maneuverability and versatility, but controlling them during trajectory tracking can be challenging due to their susceptibility to external disturbances and perturbations in their model parameters. Additionally, the UUV has four degrees of freedom underwater, but only three control inputs, making it a typical underactuated system. To address these issues, this paper introduces a novel optimize sliding mode control (OPSMC) algorithm grounded in projected perpendicular guidance (PPG). The PPG algorithm transforms the three-degree-of-freedom path trajectory control into two-degree-of-freedom heading tracking control and surge velocity tracking control by designing virtual posture angles. Optimized sliding mode control, based on sliding mode control, improves control precision and reduces control input chattering by constructing optimization functions for control inputs. During trajectory tracking, UUVs are susceptible to external environmental disturbances and perturbations in system model parameters. Disturbance observers are employed to estimate these disturbances and perturbations. Finally, MATLAB/Simulink is used for numerical simulation experiments. The simulation results demonstrate that the PPG algorithm effectively enables underactuated UUVs to achieve trajectory tracking control. The designed optimized sliding mode controller and disturbance observer enhance the control precision and robustness of the system.

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Section: Design Of Disturbance Observermentioning

confidence: 99%

“…These include OPSMC based on disturbance observer, SMC based on a disturbance observer, and SMC alone to achieve UUV trajectory tracking. Here, the SMC algorithm is consistent with the design method of SMC in [37]. We simulate it using straight and curved paths, respectively.…”

Section: Simulation Verificationmentioning

confidence: 99%

Trajectory Tracking Control of Unmanned Underwater Vehicle Based on Projected Perpendicular Guidance Method with Disturbance Observer

Liu,

Zhang,

Zhang

2024

JMSE

Self Cite

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“…Although the problems of environmental interference and ship model perturbation can be solved, the application of the back-stepping method requires differential coefficient of the virtual control law, which is easy to cause the problem of "explosion of complexity". In [4], for the purpose of reducing the computational burden, the dynamic surface control (DSC) technology is used to estimate the derivative of virtual control law, and a sliding mode control algorithm based on neural network is designed for under-actuated ships. In [5], the path following command filter sliding mode controller with robustness is proposed based on the improved dynamical virtual ship guidance algorithm.…”

Section: Introductionmentioning

confidence: 99%

Path following of under-actuated ships based on adaptive global fast terminal sliding mode control

Chen

Jiao

2023

Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023)

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In order to solve the problems of nonlinear unknown term and external environmental disturbances of the under-actuated ship motion system, an indirect control method based on adaptive global fast terminal sliding mode control (GFTSMC) algorithm is devised for path following of under-actuated ships. The path following controller consists of course guidance law and heading controller. An iterative sliding mode scheme based on nonlinear hyperbolic tangent function is introduced to design the course guidance law in order to restrict the maximum yaw rate. Then the ship's heading is controlled by heading controller, the GFTSMC algorithm is introduced to nonlinear state error feedback (NLSEF) in order to reduce the chattering. The nonlinear unknown term is estimated by radial basis function (RBF) neural network to improve the robustness and the adaptive ability of the controller. The simulation results show that the ship can follow the desired path precisely under the external environmental disturbances such as wave, wind and current, proving the effectiveness of the designed algorithm.

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“…Most cargo ships are underactuated with propellers and rudders for surge and yaw motions and without other actuators for the sway motion, which are coupled with the nonlinear ship hydrodynamic characteristics. Various control methods have been proposed for solving the path-following problem of ships, such as sliding-mode control (Zhang et al, 2022), adaptive control (Culverhouse et al, 2015), observer-based control (Liu et al, 2019), model predictive control (Liang et al, 2021), etc. These methods require an ideal and accurate mathematical model of the ship.…”

Section: Introductionmentioning

confidence: 99%

Data-driven model predictive control of underactuated ships with unknown dynamics in confined waterways

Liu

2022

J. Navigation

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Inland waterway transportation is one of the most important means to transport cargo in rivers and canals. To facilitate autonomous navigation for ships in inland waterways, this paper proposes a data-driven approach for predictions and control of underactuated ships with unknown dynamics, which integrates model predictive control (MPC) with an iterative learning control (ILC) scheme. In each iteration, kernel-based linear regressors are used to identify the relations between the evolution of ship states and control inputs based on the stored data from previous iterations and the collected data during operation, so as to build the system prediction model. The data are dynamically used to fix the prediction model over iterations, as well as to improve the controller performance until it converges. The proposed approach does not require prior knowledge regarding the hydrodynamic coefficients and ship parameters, but learns from the data instead. In addition, it exploits the advantages of MPC in handling constraints with minimised overall cost. Simulation results show that the controller could start from a nominal, linear data-driven ship model and then learn to reduce the path-following errors based on the data obtained over iterations.

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Sliding mode adaptive control for ship path following with sideslip angle observer

Cited by 26 publications

References 27 publications

Trajectory Tracking Control of Unmanned Underwater Vehicle Based on Projected Perpendicular Guidance Method with Disturbance Observer

Trajectory Tracking Control of Unmanned Underwater Vehicle Based on Projected Perpendicular Guidance Method with Disturbance Observer

Path following of under-actuated ships based on adaptive global fast terminal sliding mode control

Data-driven model predictive control of underactuated ships with unknown dynamics in confined waterways

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