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Path Following Based on Waypoints and Real-Time Obstacle Avoidance Control of an Autonomous Underwater Vehicle

机译：基于航点的实时水下航行器路径跟踪与实时避障控制

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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.
机译：本文研究了无横向和垂直驱动力的欠驱动自动水下航行器（AUV）的三维（3D）直线路径跟随和避障控制。首先，通过在运动控制器中使用两种不同的方法来设计预期的角速度。第一种是基于视线（LOS）制导律的传统方法，第二种是基于模型预测控制（MPC）的改进方法。同时，利用车载传感器检测到的障碍物信息设计了惩罚项，可以实现对未知障碍物的实时避障。然后，为克服动力学模型的不确定性和实际控制输入的饱和性，采用滑模控制（SMC）技术设计了动态控制器。最后，在仿真实验中，与两种基于LOS制导律的传统控制方法进行了比较，验证了改进控制方法的性能。由于在MPC中考虑了AUV角速度的约束，仿真结果表明，改进的控制方法采用MPC，SMC不仅提高了在接近航路点切换路径时AUV的跟踪质量并实现了实时避障，而且有效地降低了均方误差（MSE）和舵角的饱和率。因此，这种控制方法更有利于系统的稳定性并节省能源。

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