scholarly journals Adaptive barrier Lyapunov function-based obstacle avoidance control for an autonomous underwater vehicle with multiple static and moving obstacles

2022 ◽  
Vol 243 ◽  
pp. 110303
Author(s):  
Jianyu Liu ◽  
Min Zhao ◽  
Lei Qiao
2016 ◽  
Vol 39 (8) ◽  
pp. 1236-1252 ◽  
Author(s):  
Basant Kumar Sahu ◽  
Bidyadhar Subudhi

This paper presents the development of simple but powerful path-following and obstacle-avoidance control laws for an underactuated autonomous underwater vehicle (AUV). Potential function-based proportional derivative (PFPD) as well as a potential function-based augmented proportional derivative (PFAPD) control laws are developed to govern the motion of the AUV in an obstacle-rich environment. For obstacle avoidance, a mathematical potential function is used, which formulates the repulsive force between the AUV and the solid obstacles intersecting the desired path. Numerical simulations are carried out to study the efficacy of the proposed controllers and the results are observed. To reduce the values of the overshoots and steady-state errors identified due to the application of PFPD controller a PFAPD controller is designed that drives the AUV along the desired trajectory. From the simulation results, it is observed that the proposed controllers are able to drive the AUV to track the desired path, avoiding the obstacles in an obstacle-rich environment. The results are compared and it is observed that the PFAPD outperforms the PFPD to drive the AUV along the desired trajectory. It is also proved that it is not necessary to employ highly complicated controllers for solving obstacle-avoidance and path-following problems of underactuated AUVs. These problems can be solved with the application of PFAPD controllers.


Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 795 ◽  
Author(s):  
Xuliang Yao ◽  
Xiaowei Wang ◽  
Feng Wang ◽  
Le Zhang

This paper studies three-dimensional (3D) straight line path following and obstacle avoidance control for an underactuated autonomous underwater vehicle (AUV) without lateral and vertical driving forces. Firstly, the expected angular velocities are designed by using two different methods in the kinematic controller. The first one is a traditional method based on Line-of-sight (LOS) guidance law, and the second one is an improved method based on model predictive control (MPC). At the same time, a penalty item is designed by using the obstacle information detected by onboard sensors, which can realize the real-time obstacle avoidance of the unknown obstacle. Then, in order to overcome the uncertainty of the dynamics model and the saturation of actual control input, the dynamic controller is designed by using sliding mode control (SMC) technology. Finally, in the simulation experiment, the performance of the improved control method is verified by comparison with two traditional control methods based on LOS guidance law. Since the constraint of an AUV’s angular velocities are considered in MPC, simulation results show that the improved control method uses MPC, and SMC not only improves the tracking quality of the AUV when switching paths near the waypoints and realizes real-time obstacle avoidance but also effectively reduces the mean square error (MSE) and saturation rate of the rudder angle. Therefore, this control method is more conducive to the system stability and saves energy.


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