Review
Automation & Control Systems
Meng Joo Er, Huibin Gong, Yi Liu, Tianhe Liu
Summary: Underactuated autonomous underwater vehicles (AUVs) play a significant role in ocean exploration and utilization. The research on trajectory tracking and formation control methods for underactuated AUVs has become a hot topic. This survey provides an overview of intelligent trajectory tracking and formation control of underactuated AUVs, highlighting research problems, recent advances, and prospects for advanced control techniques, especially AI-based techniques.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Shiming He, Liwei Kou, Yanjun Li, Ji Xiang
Summary: This article addresses the OSTT controller design problem for AUVs with separate forces or torques for surge, heave, roll, and yaw, in the presence of hydrodynamic uncertainties and external disturbances. The effectiveness of the proposed method is illustrated by both simulation results and experimental results.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Engineering, Marine
Xuliang Yao, Feng Wang, Changshun Yuan, Jingfang Wang, Xiaowei Wang
Summary: This paper presents an interval optimization scheme for planning time-optimal paths for autonomous underwater vehicles in oceanic environments, considering the uncertainty of ocean flows. The scheme involves an outer layer using quantum-behaved particle swarm optimization to generate paths, and an inner layer calculating the path response under interval current fields. The impact of predictive uncertainty is analyzed through simulation, and the robustness of the scheme is confirmed.
Article
Automation & Control Systems
Shahab Heshmati-Alamdari, Alexandros Nikou, Dimos V. Dimarogonas
Summary: This article presents a robust nonlinear model predictive control scheme for underactuated underwater robotic vehicles to track 3-D trajectories in a constrained workspace with obstacles. The controller steers the vehicles to the desired trajectory while ensuring avoidance of obstacles and other constraints in a partially known and dynamic environment.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Ocean
Junnan Liu, Jialu Du
Summary: This paper develops a composite learning tracking control scheme for underactuated autonomous underwater vehicles (AUVs) in the presence of unknown dynamics and time-varying disturbances. Line-of-sight (LOS) tracking control and adaptive neural networks are employed to handle the underactuation and approximate the unknown dynamics of the AUVs. Stability analysis via the Lyapunov method is conducted, and nonlinear disturbance observers are constructed to estimate time-varying disturbances, verifying the effectiveness and superiority of the proposed control scheme through simulation results on an AUV.
APPLIED OCEAN RESEARCH
(2021)
Article
Engineering, Marine
Bing Huang, Bin Zhou, Sai Zhang, Cheng Zhu
Summary: This paper investigates the adaptive prescribed performance trajectory tracking control problem for underactuated underwater vehicles and proposes a control method based on command filter-based backstepping design and minimum learning parameter algorithm, effectively avoiding the complexity and computational complexity issues inherent in neural networks.
Article
Engineering, Marine
Tianqi Xie, Ye Li, Yanqing Jiang, Shuo Pang, Xuefeng Xu
Summary: A three-dimensional mobile docking control method is proposed to control an underactuated autonomous underwater vehicle (AUV) to complete a mobile docking mission. It consists of a docking position estimation method, a control strategy with a switched guidance algorithm, and an observer-based backstepping sliding mode controller.
Article
Chemistry, Multidisciplinary
Dongzhou Zhan, Huarong Zheng, Wen Xu
Summary: This paper proposes an acoustic localization-based tracking control method for AUVs to address the challenges of GPS signal absence and ocean currents' influence. The method involves deploying buoys emitting acoustic signals, using extended Kalman filter for handling uncertainties, and applying model predictive control and dead-reckoning technique for tracking controller design. Successive linearizations are employed to balance computational complexity and control performance, showing effectiveness in achieving AUV tracking control goals in simulation results.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Marine
Jin Hoe Kim, Sung Jin Yoo
Summary: This paper introduces a distributed event-driven adaptive formation control strategy for networked uncertain nonlinear autonomous underwater vehicles, achieving three-dimensional formation tracking through error transformation and neural network control, ensuring stability in the Lyapunov sense and avoiding Zeno behavior in the resulting event-triggering strategy.
Article
Computer Science, Artificial Intelligence
Levi Cai, Nathan E. McGuire, Roger Hanlon, T. Aran Mooney, Yogesh Girdhar
Summary: In-situ visual observations are essential for understanding the behavior of marine organisms and their interaction with the ecosystem. Traditional methods involve divers, tags, and remotely-operated vehicles, but autonomous underwater vehicles with cameras and embedded computers are being developed to supplement these methods. This paper introduces a new dataset, evaluates semi-supervised algorithms for underwater animal tracking, and demonstrates the real-world performance of a semi-supervised algorithm on an autonomous underwater vehicle.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2023)
Article
Automation & Control Systems
Shaobao Li, Petar Durdevic, Zhenyu Yang
Summary: This article investigates the optimal control policy learning for underactuated vertical take-off and landing (VTOL) aerial vehicles with unknown mass and inertia matrix, proposing a novel off-policy integral reinforcement learning (IRL) scheme for parameter identification and trajectory tracking.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Engineering, Marine
Hongxuan Chen, Guoyuan Tang, Shufeng Wang, Wenxuan Guo, Hui Huang
Summary: An adaptive fixed-time backstepping control method is proposed for achieving three-dimensional trajectory tracking control of an underactuated autonomous underwater vehicle (AUV) in the presence of model uncertainty and external disturbances. The dynamics of the AUV with five degrees of freedom (DOFs) are discussed, and a virtual velocity guidance law is derived using the backstepping method. The proposed control scheme demonstrates theoretical convergence of tracking error to a small bounded field within a fixed time, and simulation results verify its effectiveness and superiority.
Article
Engineering, Marine
Ji-Hong Li, Hyungjoo Kang, Min-Gyu Kim, Mun-Jik Lee, Gun Rae Cho, Han-Sol Jin
Summary: This paper presents a 3D formation control scheme for torpedo-type underactuated autonomous underwater vehicles (AUVs) by applying a virtual school concept. The formation is achieved by each individual vehicle following the trajectory of its virtual leader. The proposed method uses a potential field method for obstacle avoidance and a neural network-based adaptive scheme to approximate the vehicle's unknown nonlinear dynamics.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Automation & Control Systems
Jian Li, Jialu Du, Frank L. Lewis
Summary: This article introduces a novel distributed prescribed performance control method for multipl3D time-varying formations of AUVs, allowing for flexible presetting of formation errors within a prescribed tolerance time and error mapping transformation. It effectively deals with uncertain dynamics and unknown disturbances by converting them into a linear parametric form.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Engineering, Marine
Shaowei Rong, Huigang Wang, Huiping Li, Weitao Sun, Qingyue Gu, Juan Lei
Summary: This paper proposes a fractional-order sliding mode control method for an underactuated autonomous underwater vehicle (AUV) with random disturbances. The method includes the design of a new fractional-order sliding mode disturbance observer (FOSMDO) to estimate random disturbances and unknown AUV models, adaptive fractional sliding mode control for motion control, and a line-of-sight guidance law with time-varying look-ahead distance for path following. The effectiveness and robustness of the proposed controller are demonstrated through numeric simulations.