The trajectory tracking control problem is addressed for autonomous underwater vehicle(AUV) in marine environ?ment, with presence of the influence of the uncertain factors including ocean current disturbance, dynamic ...The trajectory tracking control problem is addressed for autonomous underwater vehicle(AUV) in marine environ?ment, with presence of the influence of the uncertain factors including ocean current disturbance, dynamic modeling uncertainty, and thrust model errors. To improve the trajectory tracking accuracy of AUV, an adaptive backstepping terminal sliding mode control based on recurrent neural networks(RNN) is proposed. Firstly, considering the inaccu?rate of thrust model of thruster, a Taylor’s polynomial is used to obtain the thrust model errors. And then, the dynamic modeling uncertainty and thrust model errors are combined into the system model uncertainty(SMU) of AUV; through the RNN, the SMU and ocean current disturbance are classified, approximated online. Finally, the weights of RNN and other control parameters are adjusted online based on the backstepping terminal sliding mode controller. In addition, a chattering?reduction method is proposed based on sigmoid function. In chattering?reduction method, the sigmoid function is used to realize the continuity of the sliding mode switching function, and the sliding mode switching gain is adjusted online based on the exponential form of the sliding mode function. Based on the Lyapu?nov theory and Barbalat’s lemma, it is theoretically proved that the AUV trajectory tracking error can quickly converge to zero in the finite time. This research proposes a trajectory tracking control method of AUV, which can e ectively achieve high?precision trajectory tracking control of AUV under the influence of the uncertain factors. The feasibility and e ectiveness of the proposed method is demonstrated with trajectory tracking simulations and pool?experi?ments of AUV.展开更多
In recent years, the weapon systems have been changing drastically because of the advancement of science technology and the change of military concept of combat. There is an unmanned system at the center of all those ...In recent years, the weapon systems have been changing drastically because of the advancement of science technology and the change of military concept of combat. There is an unmanned system at the center of all those changes. Especially, in case of maritime environment, as the center stage of combat has changed from ocean to coastal areas, it is difficult for the existing naval forces to effectively operate in shallow waters. Therefore, unmanned underwater vehicles (UUVs) are being required at an increasing pace. In this paper, we analyze the characteristics of already developed UUVs, which are the key unmanned system of the marine battlefield environment in the future. Through the analysis of development cases and the investigation of the essential technologies, the critical design issues of UUVs are elaborated. We also suggest the future directions of the UUV technologies based on the case analysis.展开更多
The advantages of using unmanned underwater vehicles in coastal ocean studies are emphasized. Two types of representative vehicles, remotely operated vehicle (ROV) and autonomous underwater vehicle (AUV) from Universi...The advantages of using unmanned underwater vehicles in coastal ocean studies are emphasized. Two types of representative vehicles, remotely operated vehicle (ROV) and autonomous underwater vehicle (AUV) from University of South Florida, are discussed. Two individual modular sensor packages designed and tested for these platforms and field measurement results are also presented. The bottom classification and albedo package, BCAP, provides fast and accurate estimates of bottom albedos, along with other parameters such as in-water remote sensing reflectance. The real-time ocean bottom optical topographer, ROBOT, reveals high-resolution 3-dimentional bottom topography for target identification. Field data and results from recent Coastal Benthic Optical Properties field campaign, 1999 and 2000, are presented. Advantages and limitations of these vehicles and applications of modular sensor packages are compared and discussed.展开更多
Tracking control has been a vital research topic in robotics.This paper presents a novel hybrid control strategy for an unmanned underwater vehicle(UUV)based on a bio-inspired neural dynamics model.An enhanced backste...Tracking control has been a vital research topic in robotics.This paper presents a novel hybrid control strategy for an unmanned underwater vehicle(UUV)based on a bio-inspired neural dynamics model.An enhanced backstepping kinematic control strategy is first developed to avoid sharp velocity jumps and provides smooth velocity commands relative to conventional methods.Then,a novel sliding mode control is proposed,which is capable of providing smooth and continuous torque commands free from chattering.In comparative studies,the proposed combined hybrid control strategy has ensured control signal smoothness,which is critical in real‐world applications,especially for a UUV that needs to operate in complex underwater environments.展开更多
In coastal environment,the motion of unmanned underwater vehicle(UUV)is influenced significantly by complex current.The operational performance of UUV can be greatly improved when the impact of ocean current is consid...In coastal environment,the motion of unmanned underwater vehicle(UUV)is influenced significantly by complex current.The operational performance of UUV can be greatly improved when the impact of ocean current is considered.A global path planning method of the static obstacle environmental space is addressed in the paper.Firstly,according to the typically coastal vortex,a model of ocean current is proposed and the influence to the motion of UUV is analyzed.Secondly,to satisfy the rapid requirement in path planning,a heuristic A*algorithm is used to design global planning path with multiple constraints.Besides,to meet the UUV’s smooth path requirement,Bezier curve theory is applied.Simulation experiments are performed to illustrate the feasibility of the algorithm in the steady current and vortex environment.展开更多
基金Basic Research Program of Ministry of Industry and Information Technology of China(Grant No.B2420133003)National Natural Science Foundation of China(Grant Nos.51779060,51679054)
文摘The trajectory tracking control problem is addressed for autonomous underwater vehicle(AUV) in marine environ?ment, with presence of the influence of the uncertain factors including ocean current disturbance, dynamic modeling uncertainty, and thrust model errors. To improve the trajectory tracking accuracy of AUV, an adaptive backstepping terminal sliding mode control based on recurrent neural networks(RNN) is proposed. Firstly, considering the inaccu?rate of thrust model of thruster, a Taylor’s polynomial is used to obtain the thrust model errors. And then, the dynamic modeling uncertainty and thrust model errors are combined into the system model uncertainty(SMU) of AUV; through the RNN, the SMU and ocean current disturbance are classified, approximated online. Finally, the weights of RNN and other control parameters are adjusted online based on the backstepping terminal sliding mode controller. In addition, a chattering?reduction method is proposed based on sigmoid function. In chattering?reduction method, the sigmoid function is used to realize the continuity of the sliding mode switching function, and the sliding mode switching gain is adjusted online based on the exponential form of the sliding mode function. Based on the Lyapu?nov theory and Barbalat’s lemma, it is theoretically proved that the AUV trajectory tracking error can quickly converge to zero in the finite time. This research proposes a trajectory tracking control method of AUV, which can e ectively achieve high?precision trajectory tracking control of AUV under the influence of the uncertain factors. The feasibility and e ectiveness of the proposed method is demonstrated with trajectory tracking simulations and pool?experi?ments of AUV.
文摘In recent years, the weapon systems have been changing drastically because of the advancement of science technology and the change of military concept of combat. There is an unmanned system at the center of all those changes. Especially, in case of maritime environment, as the center stage of combat has changed from ocean to coastal areas, it is difficult for the existing naval forces to effectively operate in shallow waters. Therefore, unmanned underwater vehicles (UUVs) are being required at an increasing pace. In this paper, we analyze the characteristics of already developed UUVs, which are the key unmanned system of the marine battlefield environment in the future. Through the analysis of development cases and the investigation of the essential technologies, the critical design issues of UUVs are elaborated. We also suggest the future directions of the UUV technologies based on the case analysis.
基金support to the University of South Florida(Grants No.0014-96-1-5013 and No.0014-97-1-0006)cooperation between Ocean University of China and University of South Florida.
文摘The advantages of using unmanned underwater vehicles in coastal ocean studies are emphasized. Two types of representative vehicles, remotely operated vehicle (ROV) and autonomous underwater vehicle (AUV) from University of South Florida, are discussed. Two individual modular sensor packages designed and tested for these platforms and field measurement results are also presented. The bottom classification and albedo package, BCAP, provides fast and accurate estimates of bottom albedos, along with other parameters such as in-water remote sensing reflectance. The real-time ocean bottom optical topographer, ROBOT, reveals high-resolution 3-dimentional bottom topography for target identification. Field data and results from recent Coastal Benthic Optical Properties field campaign, 1999 and 2000, are presented. Advantages and limitations of these vehicles and applications of modular sensor packages are compared and discussed.
基金This work is supported by the Advanced Robotic Intelligent Systems Laboratory at the University of Guelph under Natural Sciences and Engineering Research Council of Canada(NSERC).
文摘Tracking control has been a vital research topic in robotics.This paper presents a novel hybrid control strategy for an unmanned underwater vehicle(UUV)based on a bio-inspired neural dynamics model.An enhanced backstepping kinematic control strategy is first developed to avoid sharp velocity jumps and provides smooth velocity commands relative to conventional methods.Then,a novel sliding mode control is proposed,which is capable of providing smooth and continuous torque commands free from chattering.In comparative studies,the proposed combined hybrid control strategy has ensured control signal smoothness,which is critical in real‐world applications,especially for a UUV that needs to operate in complex underwater environments.
基金supported by National Natural Science Foundation (NNSF) of China under Grant 51179038
文摘In coastal environment,the motion of unmanned underwater vehicle(UUV)is influenced significantly by complex current.The operational performance of UUV can be greatly improved when the impact of ocean current is considered.A global path planning method of the static obstacle environmental space is addressed in the paper.Firstly,according to the typically coastal vortex,a model of ocean current is proposed and the influence to the motion of UUV is analyzed.Secondly,to satisfy the rapid requirement in path planning,a heuristic A*algorithm is used to design global planning path with multiple constraints.Besides,to meet the UUV’s smooth path requirement,Bezier curve theory is applied.Simulation experiments are performed to illustrate the feasibility of the algorithm in the steady current and vortex environment.
