A new method in which the consensus algorithm is used to solve the coordinate control problems of leaderless multiple autonomous underwater vehicles(multi-AUVs) with double independent Markovian switching communicat...A new method in which the consensus algorithm is used to solve the coordinate control problems of leaderless multiple autonomous underwater vehicles(multi-AUVs) with double independent Markovian switching communication topologies and time-varying delays among the underwater sensors is investigated.This is accomplished by first dividing the communication topology into two different switching parts,i.e.,velocity and position,to reduce the data capacity per data package sent between the multi-AUVs in the ocean.Then,the state feedback linearization is used to simplify and rewrite the complex nonlinear and coupled mathematical model of the AUVs into a double-integrator dynamic model.Consequently,coordinate control of the multi-AUVs is regarded as an approximating consensus problem with various time-varying delays and velocity and position topologies.Considering these factors,sufficient conditions of consensus control are proposed and analyzed and the stability of the multi-AUVs is proven by Lyapunov-Krasovskii theorem.Finally,simulation results that validate the theoretical results are presented.展开更多
A parallel neural network-based controller (PNNC) is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and i...A parallel neural network-based controller (PNNC) is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and it is different from normal adaptive neural network controller in structure. Owing to the introduction of the self-learning part, on-line learning can be performed without sample data in several sample periods, resulting in high learning speed of the controller and good control performance. The desired-state programmer is utilized to obtain better learning samples of the neural network to keep the stability of the controller. The developed controller is applied to the 4-degree of freedom control of the AUV “IUV- IV” and is successful on the simulation platform. The control performance is also compared with that of neural network controller with different structures such as normal adaptive neural network and different learning methods. Current effects and surge velocity control are also included to demonstrate the controller' s performance. It is shown that the PNNC has a great possibility to solve the problems in the control system design of underwater vehicles.展开更多
As the mission needs of the autonomous underwater vehicles(AUV) have become increasingly varied and complex,the AUVs are developing in the direction of systematism, multifunction, and clustering technology, which prom...As the mission needs of the autonomous underwater vehicles(AUV) have become increasingly varied and complex,the AUVs are developing in the direction of systematism, multifunction, and clustering technology, which promotes the progress of key technologies and proposes a series of technical problems. Therefore, it is necessary to make systemic analysis and in-depth study for the progress of AUV's key technologies and innovative applications. The multi-functional mission needs and its key technologies involved in complex sea conditions are pointed out through analyzing the domestic and foreign technical programs, functional characteristics and future development plans. Furthermore, the overall design of a multi-moving state AUV is proposed. Then, technical innovations of the key technologies, such as thrust vector, propeller design, kinematics and dynamics, navigation control, and ambient flow field characteristics, are made, combining with the structural characteristics and motion characteristics of the new multi-moving state AUV. The results verify the good performance of the multi-moving state AUV and provide a theoretical guidance and technical support for the design of new AUV in real complex sea conditions.展开更多
In order to achieve the functional requirements of multi-moving state, a new autonomous underwater vehicle(AUV) provided with the functions such as the submarine vectorial thrust, landing on the sea bottom, wheel driv...In order to achieve the functional requirements of multi-moving state, a new autonomous underwater vehicle(AUV) provided with the functions such as the submarine vectorial thrust, landing on the sea bottom, wheel driving on the ground and crawling on the ground was designed. Then five new theories and methods were proposed about the motion mechanism of the AUV such as vectorial thruster technology, design of a new wheel propeller, kinematics and dynamics, navigation control and the ambient flow field in complex sea conditions, which can all conquer conventional technique shortages and predict the multi-moving state performance under wave disturbance. The theoretical research can realize the results such as a vectorial transmission shaft with the characteristics of spatial deflexion and continual circumgyratetion, parameterized design of the new wheel propeller with preferable open-water performance and intensity characteristics satisfying multi-moving state requirements, motion computation and kinetic analysis of AUV's arbitrary postures under wave disturbance, a second-order sliding mode controller with double-loop structure based on dynamic boundary layer that ensures AUV's trajectory high-precision tracking performance under wave disturbance, fast and exact prediction of the ambient flow field characteristics and the interaction mechanism between AUV hull and wheel propellers. The elaborate data obtained from the theoretical research can provide an important theoretical guidance and technical support for the manufacture of experimental prototype.展开更多
The bottom-following problem for underactuated autonomous underwater vehicles(AUV) was addressed by a new type of nonlinear decoupling control law.The vertical bottom-following error and pitch angle error are stabiliz...The bottom-following problem for underactuated autonomous underwater vehicles(AUV) was addressed by a new type of nonlinear decoupling control law.The vertical bottom-following error and pitch angle error are stabilized by means of the stern plane,and the thruster is left to stabilize the longitudinal bottom-following error and forward speed.In order to better meet the need of engineering applications,working characteristics of the actuators were sufficiently considered to design the proposed controller.Different from the traditional method,the methodology used to solve the problem is generated by AUV model without a reference orientation,and it deals explicitly with vehicle dynamics and the geometric characteristics of the desired tracking bottom curve.The estimation of systemic uncertainties and disturbances and the pitch velocity PE(persistent excitation) conditions are not required.The stability analysis is given by Lyapunov theorem.Simulation results of a full nonlinear hydrodynamic AUV model are provided to validate the effectiveness and robustness of the proposed controller.展开更多
A cooperative navigation algorithm for a group of autonomous underwater vehicles is proposed on the basis of motion radius vector estimation.Combined the dead reckoning data with the mutual range data through an acous...A cooperative navigation algorithm for a group of autonomous underwater vehicles is proposed on the basis of motion radius vector estimation.Combined the dead reckoning data with the mutual range data through an acoustic communication network among the group members, the relative positioning problem can be solved. A novel approach for solving the relative positioning is presented by using a recursive trigonometry technique and extended Kalman filter(EKF). Simulation results verify the correctness and effectiveness of this navigation method.展开更多
Autonomous underwater vehicles (AUVs) navigating on the sea surface are usually required to complete the communication tasks in complex sea conditions.The movement forms and flow field characteristics of a multi-movin...Autonomous underwater vehicles (AUVs) navigating on the sea surface are usually required to complete the communication tasks in complex sea conditions.The movement forms and flow field characteristics of a multi-moving state AUV navigating in head sea at high speed were studied.The mathematical model on longitudinal motion of the high-speed AUV in head sea was established with considering the hydrodynamic lift based on strip theory,which was solved to get the heave and pitch of the AUV by Gaussian elimination method.Based on this,computational fluid dynamics (CFD) method was used to establish the mathematical model of the unsteady viscous flow around the AUV with considering free surface effort by using the Reynolds-averaged Navier-Stokes (RANS) equations,shear-stress transport (SST) k-w model and volume of fluid (VOF) model.The three-dimensional numerical wave in the computational field was realized through defining the unsteady inlet boundary condition.The motion forms of the AUV navigating in head sea at high speed were carried out by the program source code of user-defined function (UDF) based on dynamic mesh.The hydrodynamic parameters of the AUV such as drag,lift,pitch torque,velocity,pressure,and wave profile were got,which reflect well the real ambient flow field of the AUV navigating in head sea at high speed.The computational wave profile agrees well with the experimental phenomenon of a wave-piercing surface vehicle.The force law of the AUV under the impacts of waves was analyzed qualitatively and quantitatively,which provides an effective theoretical guidance and technical support for the dynamics research and shape design of the AUV in real complex environment.展开更多
S-surface control has proven to be an effective means for motion control of underwater autonomous vehicles(AUV).However there are still problems maintaining steady precision of course due to the constant need to adjus...S-surface control has proven to be an effective means for motion control of underwater autonomous vehicles(AUV).However there are still problems maintaining steady precision of course due to the constant need to adjust parameters,especially where there are disturbing currents.Thus an intelligent integral was introduced to improve precision.An expert S-surface control was developed to tune the parameters on-line,based on the expert system,it provides S-surface control according to practical experience and control knowledge.To prevent control output over-compensation,a fuzzy neural network was included to adjust the production rules to the knowledge base.Experiments were conducted on an AUV simulation platform,and the results show that the expert S-surface controller performs better than an S-surface controller in environments with currents,producing good steady precision of course in a robust way.展开更多
Sonar image processing system is an important intelligent system of Autonomous Un-derwater Vehicle.Based on TMS320C30 high speed DSP,it is used to realize sonar imagecompression and underwater object detections includ...Sonar image processing system is an important intelligent system of Autonomous Un-derwater Vehicle.Based on TMS320C30 high speed DSP,it is used to realize sonar imagecompression and underwater object detections including obstacle recognition in real time.Inthis paper,the software and hardware designs of this system are introduced and the experi-mental results are given.展开更多
Autonomous Underwater Vehicles (AUV’s) are considered as advanced classes of vehicles, capable of performing pre-established missions without physical communication with the ground or human assistance. The research a...Autonomous Underwater Vehicles (AUV’s) are considered as advanced classes of vehicles, capable of performing pre-established missions without physical communication with the ground or human assistance. The research and development of this type of vehicles have been motivated, due to its excellent characteristics, ideal to the military, scientific and industrial sectors. Thus, the objective of this paper is to study fluid flow behavior past over AUV’s, without and with control surfaces (rudders), by Computational Fluid-Dynamics (CFD), aiming to obtain information about the impact of the operating depth and control surfaces on the vehicle's hydrodynamics, in order to help researchers and designers of this class of vehicles. Results of the drag coefficient, pressure, velocity and streamlines distribution around the vehicles are presented and analyzed.展开更多
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
This paper presents a bio-inspired geomagnetic navigation method for autonomous underwater vehicle(AUV) without using any a priori geomagnetic information. Firstly, the multi-objective search problem is raised. Second...This paper presents a bio-inspired geomagnetic navigation method for autonomous underwater vehicle(AUV) without using any a priori geomagnetic information. Firstly, the multi-objective search problem is raised. Secondly, the geomagnetic navigation model is established by constructing a cost function. Then, by taking into consideration the biological magneto-taxis movement behavior for the geomagnetic environment stimulus, the multiobjective evolutionary search algorithm is derived to describe the search process. Finally, compared to the state-of-the-art, the proposed method presents better robustness. The simulation results demonstrate the reliability and feasibility of the proposed method.展开更多
Qianlong-Ⅱ is a fully autonomous underwater vehicle designed for the investigation of submarine resources,particularly polymetallic sulfides. It was used to successfully explore hydrothermal fields on the Southwest I...Qianlong-Ⅱ is a fully autonomous underwater vehicle designed for the investigation of submarine resources,particularly polymetallic sulfides. It was used to successfully explore hydrothermal fields on the Southwest Indian Ridge. Here, we summarized the exploration of hydrothermal systems using Qianlong-Ⅱ, including detailed descriptions of its implementation along with the systems used for data management and fast mapping. We also introduced a method to remove platform magnetic interference using magnetic data while Qianlong-Ⅱ is spinning. Based on hydrothermal anomalies collected by Qianlong-Ⅱ, we developed a rapid method for locating hydrothermal vents. Taking one dive as an example, we systemically demonstrated the process for analyzing hydrothermal survey data to locate hydrothermal vents.展开更多
Autonomous underwater vehicles (AUVs) navigating in complex sea conditions usually require a strong control system to keep the fastness and stability. The nonlinear trajectory tracking control system of a new AUV in c...Autonomous underwater vehicles (AUVs) navigating in complex sea conditions usually require a strong control system to keep the fastness and stability. The nonlinear trajectory tracking control system of a new AUV in complex sea conditions was presented. According to the theory of submarines,the six-DOF kinematic and dynamic models were decomposed into two mutually non-coupled vertical and horizontal plane subsystems. Then,different sliding mode control algorithms were used to study the trajectory tracking control. Because the yaw angle and yaw angle rate rather than the displacement of the new AUV can be measured directly on the horizontal plane,the sliding mode control algorithm combining cross track error method and line of sight method was used to fulfill its high-precision trajectory tracking control in the complex sea conditions. As the vertical displacement of the new AUV can be measured,in order to achieve the tracking of time-varying depth signal,a stable sliding mode controller was designed based on the single-input multi-state system,which took into account the characteristic of the hydroplane and the amplitude and rate constraints of the hydroplane angle. Moreover,the application of dynamic boundary layer can improve the robustness and control accuracy of the system. The computational results show that the designed sliding mode control systems of the horizontal and vertical planes can ensure the trajectory tracking performance and accuracy of the new AUV in complex sea conditions. The impacts of currents and waves on the sliding mode controller of the new AUV were analyzed qualitatively and quantitatively by comparing the trajectory tracking performance of the new AUV in different sea conditions,which provides an effective theoretical guidance and technical support for the control system design of the new AUV in real complex environment.展开更多
The stability of the motion control system is one of the decisive factors of the control quality for Autonomous Underwater Vehicle(AUV).The divergence of control,which the unstable system may be brought about,is fat...The stability of the motion control system is one of the decisive factors of the control quality for Autonomous Underwater Vehicle(AUV).The divergence of control,which the unstable system may be brought about,is fatal to the operation of AUV.The stability analysis of the PD and S-surface speed controllers based on the Lyapunov's direct method is proposed in this paper.After decoupling the six degree-of-freedom(DOF)motions of the AUV,the axial dynamic behavior is discussed and the condition is deduced,in which the parameters selection within stability domain can guarantee the system asymptotically stable.The experimental results in a tank and on the sea have successfully verified the algorithm reliability,which can be served as a good reference for analyzing other AUV nonlinear control systems.展开更多
This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater ve...This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion decoupling.At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller.Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.51679057,51309067,and 51609048)the Outstanding Youth Science Foundation of Heilongjiang Providence of China(Grant No.JC2016007)the Natural Science Foundation of Heilongjiang Province,China(Grant No.E2016020)
文摘A new method in which the consensus algorithm is used to solve the coordinate control problems of leaderless multiple autonomous underwater vehicles(multi-AUVs) with double independent Markovian switching communication topologies and time-varying delays among the underwater sensors is investigated.This is accomplished by first dividing the communication topology into two different switching parts,i.e.,velocity and position,to reduce the data capacity per data package sent between the multi-AUVs in the ocean.Then,the state feedback linearization is used to simplify and rewrite the complex nonlinear and coupled mathematical model of the AUVs into a double-integrator dynamic model.Consequently,coordinate control of the multi-AUVs is regarded as an approximating consensus problem with various time-varying delays and velocity and position topologies.Considering these factors,sufficient conditions of consensus control are proposed and analyzed and the stability of the multi-AUVs is proven by Lyapunov-Krasovskii theorem.Finally,simulation results that validate the theoretical results are presented.
文摘A parallel neural network-based controller (PNNC) is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and it is different from normal adaptive neural network controller in structure. Owing to the introduction of the self-learning part, on-line learning can be performed without sample data in several sample periods, resulting in high learning speed of the controller and good control performance. The desired-state programmer is utilized to obtain better learning samples of the neural network to keep the stability of the controller. The developed controller is applied to the 4-degree of freedom control of the AUV “IUV- IV” and is successful on the simulation platform. The control performance is also compared with that of neural network controller with different structures such as normal adaptive neural network and different learning methods. Current effects and surge velocity control are also included to demonstrate the controller' s performance. It is shown that the PNNC has a great possibility to solve the problems in the control system design of underwater vehicles.
基金Supported by National High Technology Research and Development Program of China (863 Program) (2007AA809502C) National Natural Science Foundation of China (50979093) Program for New Century Excellent Talents in University (NCET-06-0877)
基金Project(ZR2014EEP019) supported by the Natural Science Foundation of Shandong Province,ChinaProject(51505491) supported by the National Natural Science Foundation of China
文摘As the mission needs of the autonomous underwater vehicles(AUV) have become increasingly varied and complex,the AUVs are developing in the direction of systematism, multifunction, and clustering technology, which promotes the progress of key technologies and proposes a series of technical problems. Therefore, it is necessary to make systemic analysis and in-depth study for the progress of AUV's key technologies and innovative applications. The multi-functional mission needs and its key technologies involved in complex sea conditions are pointed out through analyzing the domestic and foreign technical programs, functional characteristics and future development plans. Furthermore, the overall design of a multi-moving state AUV is proposed. Then, technical innovations of the key technologies, such as thrust vector, propeller design, kinematics and dynamics, navigation control, and ambient flow field characteristics, are made, combining with the structural characteristics and motion characteristics of the new multi-moving state AUV. The results verify the good performance of the multi-moving state AUV and provide a theoretical guidance and technical support for the design of new AUV in real complex sea conditions.
基金Project(51505491)supported by the National Natural Science Foundation of ChinaProject(ZR2014EEP019)supported by the Natural Science Foundation of Shandong Province,China
文摘In order to achieve the functional requirements of multi-moving state, a new autonomous underwater vehicle(AUV) provided with the functions such as the submarine vectorial thrust, landing on the sea bottom, wheel driving on the ground and crawling on the ground was designed. Then five new theories and methods were proposed about the motion mechanism of the AUV such as vectorial thruster technology, design of a new wheel propeller, kinematics and dynamics, navigation control and the ambient flow field in complex sea conditions, which can all conquer conventional technique shortages and predict the multi-moving state performance under wave disturbance. The theoretical research can realize the results such as a vectorial transmission shaft with the characteristics of spatial deflexion and continual circumgyratetion, parameterized design of the new wheel propeller with preferable open-water performance and intensity characteristics satisfying multi-moving state requirements, motion computation and kinetic analysis of AUV's arbitrary postures under wave disturbance, a second-order sliding mode controller with double-loop structure based on dynamic boundary layer that ensures AUV's trajectory high-precision tracking performance under wave disturbance, fast and exact prediction of the ambient flow field characteristics and the interaction mechanism between AUV hull and wheel propellers. The elaborate data obtained from the theoretical research can provide an important theoretical guidance and technical support for the manufacture of experimental prototype.
基金Project(61174047) supported by the National Natural Science Foundation of ChinaProject(20102304110003) supported by the Doctoral Fund of Ministry of Education of ChinaProject(51316080301) supported by Advanced Research
文摘The bottom-following problem for underactuated autonomous underwater vehicles(AUV) was addressed by a new type of nonlinear decoupling control law.The vertical bottom-following error and pitch angle error are stabilized by means of the stern plane,and the thruster is left to stabilize the longitudinal bottom-following error and forward speed.In order to better meet the need of engineering applications,working characteristics of the actuators were sufficiently considered to design the proposed controller.Different from the traditional method,the methodology used to solve the problem is generated by AUV model without a reference orientation,and it deals explicitly with vehicle dynamics and the geometric characteristics of the desired tracking bottom curve.The estimation of systemic uncertainties and disturbances and the pitch velocity PE(persistent excitation) conditions are not required.The stability analysis is given by Lyapunov theorem.Simulation results of a full nonlinear hydrodynamic AUV model are provided to validate the effectiveness and robustness of the proposed controller.
基金Sponsored by National Natural Foundation (50979093)the High Technology Research and Development Program of China (863 Program)( 2007AA809502C)Program for New Century Excellent Talents in University (NCET-06-0877)
文摘A cooperative navigation algorithm for a group of autonomous underwater vehicles is proposed on the basis of motion radius vector estimation.Combined the dead reckoning data with the mutual range data through an acoustic communication network among the group members, the relative positioning problem can be solved. A novel approach for solving the relative positioning is presented by using a recursive trigonometry technique and extended Kalman filter(EKF). Simulation results verify the correctness and effectiveness of this navigation method.
基金Project(2006AA09Z235)supported by the National High Technology Research and Development Program of ChinaProject(CX2009B003)supported by Hunan Provincial Innovation Foundation For Postgraduate,China
文摘Autonomous underwater vehicles (AUVs) navigating on the sea surface are usually required to complete the communication tasks in complex sea conditions.The movement forms and flow field characteristics of a multi-moving state AUV navigating in head sea at high speed were studied.The mathematical model on longitudinal motion of the high-speed AUV in head sea was established with considering the hydrodynamic lift based on strip theory,which was solved to get the heave and pitch of the AUV by Gaussian elimination method.Based on this,computational fluid dynamics (CFD) method was used to establish the mathematical model of the unsteady viscous flow around the AUV with considering free surface effort by using the Reynolds-averaged Navier-Stokes (RANS) equations,shear-stress transport (SST) k-w model and volume of fluid (VOF) model.The three-dimensional numerical wave in the computational field was realized through defining the unsteady inlet boundary condition.The motion forms of the AUV navigating in head sea at high speed were carried out by the program source code of user-defined function (UDF) based on dynamic mesh.The hydrodynamic parameters of the AUV such as drag,lift,pitch torque,velocity,pressure,and wave profile were got,which reflect well the real ambient flow field of the AUV navigating in head sea at high speed.The computational wave profile agrees well with the experimental phenomenon of a wave-piercing surface vehicle.The force law of the AUV under the impacts of waves was analyzed qualitatively and quantitatively,which provides an effective theoretical guidance and technical support for the dynamics research and shape design of the AUV in real complex environment.
基金Supported by the National Natural Science Foundation of China under Grant No.50579007
文摘S-surface control has proven to be an effective means for motion control of underwater autonomous vehicles(AUV).However there are still problems maintaining steady precision of course due to the constant need to adjust parameters,especially where there are disturbing currents.Thus an intelligent integral was introduced to improve precision.An expert S-surface control was developed to tune the parameters on-line,based on the expert system,it provides S-surface control according to practical experience and control knowledge.To prevent control output over-compensation,a fuzzy neural network was included to adjust the production rules to the knowledge base.Experiments were conducted on an AUV simulation platform,and the results show that the expert S-surface controller performs better than an S-surface controller in environments with currents,producing good steady precision of course in a robust way.
基金the High Technology Research and Development Programme of china.
文摘Sonar image processing system is an important intelligent system of Autonomous Un-derwater Vehicle.Based on TMS320C30 high speed DSP,it is used to realize sonar imagecompression and underwater object detections including obstacle recognition in real time.Inthis paper,the software and hardware designs of this system are introduced and the experi-mental results are given.
基金Brazilian Research Agencies CNPq,CAPES and FINEP for supporting this work
文摘Autonomous Underwater Vehicles (AUV’s) are considered as advanced classes of vehicles, capable of performing pre-established missions without physical communication with the ground or human assistance. The research and development of this type of vehicles have been motivated, due to its excellent characteristics, ideal to the military, scientific and industrial sectors. Thus, the objective of this paper is to study fluid flow behavior past over AUV’s, without and with control surfaces (rudders), by Computational Fluid-Dynamics (CFD), aiming to obtain information about the impact of the operating depth and control surfaces on the vehicle's hydrodynamics, in order to help researchers and designers of this class of vehicles. Results of the drag coefficient, pressure, velocity and streamlines distribution around the vehicles are presented and analyzed.
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.
基金supported by the National Natural Science Foundation of China(5137917651179156)
文摘This paper presents a bio-inspired geomagnetic navigation method for autonomous underwater vehicle(AUV) without using any a priori geomagnetic information. Firstly, the multi-objective search problem is raised. Secondly, the geomagnetic navigation model is established by constructing a cost function. Then, by taking into consideration the biological magneto-taxis movement behavior for the geomagnetic environment stimulus, the multiobjective evolutionary search algorithm is derived to describe the search process. Finally, compared to the state-of-the-art, the proposed method presents better robustness. The simulation results demonstrate the reliability and feasibility of the proposed method.
基金The Technology Upgrading and Scientific Applications of the 4 500 m Depth Rated Qianlong Ⅱ AUV under contract No.2017YFC0306803the National Key R&D Program of China under contract No.2018YFC0309901the COMRA Major Project under contract Nos DY135-S1-01-06 and DY135-S1-01-01
文摘Qianlong-Ⅱ is a fully autonomous underwater vehicle designed for the investigation of submarine resources,particularly polymetallic sulfides. It was used to successfully explore hydrothermal fields on the Southwest Indian Ridge. Here, we summarized the exploration of hydrothermal systems using Qianlong-Ⅱ, including detailed descriptions of its implementation along with the systems used for data management and fast mapping. We also introduced a method to remove platform magnetic interference using magnetic data while Qianlong-Ⅱ is spinning. Based on hydrothermal anomalies collected by Qianlong-Ⅱ, we developed a rapid method for locating hydrothermal vents. Taking one dive as an example, we systemically demonstrated the process for analyzing hydrothermal survey data to locate hydrothermal vents.
基金Project(2006AA09Z235) supported by the National High Technology Research and Development Program of ChinaProject(CX2009B003) supported by Hunan Provincial Innovation Foundation For Postgraduates,China
文摘Autonomous underwater vehicles (AUVs) navigating in complex sea conditions usually require a strong control system to keep the fastness and stability. The nonlinear trajectory tracking control system of a new AUV in complex sea conditions was presented. According to the theory of submarines,the six-DOF kinematic and dynamic models were decomposed into two mutually non-coupled vertical and horizontal plane subsystems. Then,different sliding mode control algorithms were used to study the trajectory tracking control. Because the yaw angle and yaw angle rate rather than the displacement of the new AUV can be measured directly on the horizontal plane,the sliding mode control algorithm combining cross track error method and line of sight method was used to fulfill its high-precision trajectory tracking control in the complex sea conditions. As the vertical displacement of the new AUV can be measured,in order to achieve the tracking of time-varying depth signal,a stable sliding mode controller was designed based on the single-input multi-state system,which took into account the characteristic of the hydroplane and the amplitude and rate constraints of the hydroplane angle. Moreover,the application of dynamic boundary layer can improve the robustness and control accuracy of the system. The computational results show that the designed sliding mode control systems of the horizontal and vertical planes can ensure the trajectory tracking performance and accuracy of the new AUV in complex sea conditions. The impacts of currents and waves on the sliding mode controller of the new AUV were analyzed qualitatively and quantitatively by comparing the trajectory tracking performance of the new AUV in different sea conditions,which provides an effective theoretical guidance and technical support for the control system design of the new AUV in real complex environment.
基金supported by the National High Technology Development Program of China(863Program,Grant No.2008AA092301)the Fundamental Research Foundation of Harbin Engineering University(Grant No.HEUFT08001)the Postdoctoral Science Foundation of China(Grant No.20080440838)
文摘The stability of the motion control system is one of the decisive factors of the control quality for Autonomous Underwater Vehicle(AUV).The divergence of control,which the unstable system may be brought about,is fatal to the operation of AUV.The stability analysis of the PD and S-surface speed controllers based on the Lyapunov's direct method is proposed in this paper.After decoupling the six degree-of-freedom(DOF)motions of the AUV,the axial dynamic behavior is discussed and the condition is deduced,in which the parameters selection within stability domain can guarantee the system asymptotically stable.The experimental results in a tank and on the sea have successfully verified the algorithm reliability,which can be served as a good reference for analyzing other AUV nonlinear control systems.
基金supported by the National Natural Science Foundation of China (6197317561973172)Tianjin Natural Science Foundation (19JCZDJC32800)。
文摘This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion decoupling.At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller.Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.