Active disturbance rejection control for ship path following with Euler method

Zhang, Hugan; Zhang, Xianku; Cao, Tian; Bu, Renxiang

doi:10.1016/j.oceaneng.2021.110516

Cited by 19 publications

(4 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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%

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

Liu,

Zhang,

Zhang

2024

JMSE

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Design Of Disturbance Observermentioning

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

View full text Add to dashboard Cite

show abstract

“…For the former, the light-of-sight (LOS) guidance was widely applied because of its high precision and simplicity [5][6][7][8]. For the latter, fruitful methods were proposed and applied to controller design, such as PID control [9,10], fuzzy control [11][12][13], adaptive control [14,15], active disturbances rejection control [16,17], sliding mode control [18,19], and backstepping control [20][21][22]. In [23], considering the path-following control under unknown environment disturbances, the modified integral LOS guidance law and the adaptive sliding mode control law are developed, realizing the desired path following.…”

Section: Introductionmentioning

confidence: 99%

A Deep Reinforcement Learning-Based Path-Following Control Scheme for an Uncertain Under-Actuated Autonomous Marine Vehicle

Qu,

Jiang,

Zhang

et al. 2023

JMSE

View full text Add to dashboard Cite

In this article, a deep reinforcement learning-based path-following control scheme is established for an under-actuated autonomous marine vehicle (AMV) in the presence of model uncertainties and unknown marine environment disturbances is presented. By virtue of light-of-sight guidance, a surge-heading joint guidance method is developed within the kinematic level, thereby enabling the AMV to follow the desired path accurately. Within the dynamic level, model uncertainties and time-varying environment disturbances are taken into account, and the reinforcement learning control method using the twin-delay deep deterministic policy gradient (TD3) is developed for the under-actuated vehicle, where path-following actions are generated via the state space and hybrid rewards. Additionally, actor-critic networks are developed using the long-short time memory (LSTM) network, and the vehicle can successfully make a decision by the aid of historical states, thus enhancing the convergence rate of dynamic controllers. Simulation results and comprehensive comparisons on a prototype AMV demonstrate the remarkable effectiveness and superiority of the proposed LSTM-TD3-based path-following control scheme.

show abstract

“…Up to now, some researches have already achieved a lot in this field. In [1,2], the ship's future position is predicted based on model predictive control (MPC) method, and an active disturbance rejection controller is designed. But the controller lacks adaptability in complex sea conditions.…”

Section: Introductionmentioning

confidence: 99%

“…1 and k 2 are positive design parameters. e  are on the same order of magnitude, which is more conducive to the controller design.…”

mentioning

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)

View full text Add to dashboard Cite

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.

show abstract

Active disturbance rejection control for ship path following with Euler method

Cited by 19 publications

References 29 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

A Deep Reinforcement Learning-Based Path-Following Control Scheme for an Uncertain Under-Actuated Autonomous Marine Vehicle

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

Contact Info

Product

Resources

About