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
In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwa...In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a nnmerical solution of a nonlinear optimal control problem （NOCP）. An energy performance index as a cost function, which should be minimized, was defmed. The resulting problem was a two-point boundary value problem （TPBVP）. A genetic algorithm （GA）, particle swarm optimization （PSO）, and ant colony optimization （ACO） algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.展开更多
To provide a simulation system platform for designing and debugging a small autonomous underwater vehicle＇s （AUV） motion controller, a six-degree of freedom （6-DOF） dynamic model for AUV controlled by thruster an...To provide a simulation system platform for designing and debugging a small autonomous underwater vehicle＇s （AUV） motion controller, a six-degree of freedom （6-DOF） dynamic model for AUV controlled by thruster and fins with appendages is examined. Based on the dynamic model, a simulation system for the AUV＇s motion is established. The different kinds of typical motions are simulated to analyze the motion performance and the maneuverability of the AUV. In order to evaluate the influences of appendages on the motion performance of the AUV, simulations of the AUV with and without appendages are performed and compared. The results demonstrate the AUV has good maneuverability with and without appendages.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
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
Obstacle avoidance becomes a very challenging task for an autonomous underwater vehicle(AUV)in an unknown underwater environment during exploration process.Successful control in such case may be achieved using the mod...Obstacle avoidance becomes a very challenging task for an autonomous underwater vehicle(AUV)in an unknown underwater environment during exploration process.Successful control in such case may be achieved using the model-based classical control techniques like PID and MPC but it required an accurate mathematical model of AUV and may fail due to parametric uncertainties,disturbance,or plant model mismatch.On the other hand,model-free reinforcement learning(RL)algorithm can be designed using actual behavior of AUV plant in an unknown environment and the learned control may not get affected by model uncertainties like a classical control approach.Unlike model-based control model-free RL based controller does not require to manually tune controller with the changing environment.A standard RL based one-step Q-learning based control can be utilized for obstacle avoidance but it has tendency to explore all possible actions at given state which may increase number of collision.Hence a modified Q-learning based control approach is proposed to deal with these problems in unknown environment.Furthermore,function approximation is utilized using neural network(NN)to overcome the continuous states and large statespace problems which arise in RL-based controller design.The proposed modified Q-learning algorithm is validated using MATLAB simulations by comparing it with standard Q-learning algorithm for single obstacle avoidance.Also,the same algorithm is utilized to deal with multiple obstacle avoidance problems.展开更多
A high-efficiency propeller can enable a long mission duration for autonomous underwater vehicles(AUVs).In this study,a new method with OpenProp coupled with computational fluid dynamics was developed to design a prop...A high-efficiency propeller can enable a long mission duration for autonomous underwater vehicles(AUVs).In this study,a new method with OpenProp coupled with computational fluid dynamics was developed to design a propeller for an Explorer100 AUV.The towed system simulation of the AUV was used to measure the nominal wake,and a self-propulsion simulation was used to measure the effective wake at the disc plane just in front of a propeller.Two propellers referring to the nominal wake(propeller 1)and effective wake(propeller 2)were designed with OpenProp and appended with the AUV for self-propulsion simulations,respectively.Through the numerical simulation of the AUV self-propulsion tests,the cruising velocity of AUV was obtained.The flow characteristics of the self-propulsion in pressure and velocity contours were also analyzed.The propeller designed with an effective wake improved the thrust,velocity,and efficiency by approximately 11.3%,6.7%,and 2.5%,respectively,as compared with those with a nominal wake.The cruising velocity of the final designed propeller for the Explorer100 AUV improved by 21.8%,as compared to that of the original propeller from the AUV free-running tests.展开更多
Autonomous Underwater Vehicles （AUVs） are capable of conducting various underwater missions and marine tasks over long periods of time. In this study, a novel conflict-free motion-planning framework is introduced. T...Autonomous Underwater Vehicles （AUVs） are capable of conducting various underwater missions and marine tasks over long periods of time. In this study, a novel conflict-free motion-planning framework is introduced. This framework enhances AUV mission performance by completing the maximum number of highest priority tasks in a limited time through a large-scale waypoint cluttered operating field and ensuring safe deployment during the mission. The proposed combinatorial route-path-planner model takes advantage of the Biogeography- Based Optimization （BBO） algorithm to satisfy the objectives of both higher- and lower-level motion planners and guarantee the maximization of mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios, including cost constraints in time-varying operating fields. To demonstrate the reliability of the proposed model, the performance of each motion planner is separately assessed and statistical analysis is conducted to evaluate the total performance of the entire model. The simulation results indicate the stability of the proposed model and the feasibility of its application to real-time experiments.展开更多
In view of the characteristics of underwater navigation, the simulation platform of navigation system for autonomous underwater vehicle has been developed based on Windows platform. The system architecture, net commun...In view of the characteristics of underwater navigation, the simulation platform of navigation system for autonomous underwater vehicle has been developed based on Windows platform. The system architecture, net communication and the information flow are discussed. The methods of software realization and some key techniques of the Vehicle Computer and the Navigation Equipment Computer are introduced in particular. The software design of Terrain Matching Computer is introduced also. The simulation platform is verified and analyzed through simulation. The results show that the architecture of the platform is reasonable and reliable, and the mathematic models and simulation algorithms of sub-systems are also valid and practicable.展开更多
Robust and efficient AUV path planning is a key element for persistence AUV maneuvering in variable underwater environments. To develop such a path planning system, in this study, differential evolution(DE) algorithm ...Robust and efficient AUV path planning is a key element for persistence AUV maneuvering in variable underwater environments. To develop such a path planning system, in this study, differential evolution(DE) algorithm is employed. The performance of the DE-based planner in generating time-efficient paths to direct the AUV from its initial conditions to the target of interest is investigated within a complexed 3D underwater environment incorporated with turbulent current vector fields, coastal area,islands, and static/dynamic obstacles. The results of simulations indicate the inherent efficiency of the DE-based path planner as it is capable of extracting feasible areas of a real map to determine the allowed spaces for the vehicle deployment while coping undesired current disturbances, exploiting desirable currents, and avoiding collision boundaries in directing the vehicle to its destination. The results are implementable for a realistic scenario and on-board real AUV as the DE planner satisfies all vehicular and environmental constraints while minimizing the travel time/distance, in a computationally efficient manner.展开更多
Up to now, some technology of neural networks are developed to solve the non-linearity of researched objects and to implement the adaptive control in many engineering fields, and some good results were achieved. Thoug...Up to now, some technology of neural networks are developed to solve the non-linearity of researched objects and to implement the adaptive control in many engineering fields, and some good results were achieved. Though it puts some questions over to design application structure with neural networks, it is really unknowable about the study mechanism of those. But, the importance of study ratio is widely realized by many scientists now, and some methods on the modification of that are provided. The main subject is how to improve the stability and how to increase the convergent rate of networks by defining a good form of the study ratio. Here a new algorithm named LDBP (least disturbance BP algorithm) is proposed to calculate the ratio online according to the output errors, the weights of network and the input values. The algorithm is applied to the control of an autonomous underwater vehicle designed by HEU. The experimental results show that the algorithm has good performance and the controller designed based on it is fine.展开更多
A series of experimental studies of the innovative propulsor named Collective and Cyclic Pitch Propeller(CCPP) applied to an underwater vehicle were designed and performed at the Australian Maritime College, Universit...A series of experimental studies of the innovative propulsor named Collective and Cyclic Pitch Propeller(CCPP) applied to an underwater vehicle were designed and performed at the Australian Maritime College, University of Tasmania. The bollard pull and captive model tests were conducted to investigate the characteristics of CCPP and to examine the effect of different parameter settings to its performance. The results show that the CCPP is able to generate effective manoeuvring forces in various operational condition. In addition, the obtained results in the form of force coefficients provide a useful empirical model for the simulation and control of an underwater vehicle equipped with this propulsor.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In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a nnmerical solution of a nonlinear optimal control problem （NOCP）. An energy performance index as a cost function, which should be minimized, was defmed. The resulting problem was a two-point boundary value problem （TPBVP）. A genetic algorithm （GA）, particle swarm optimization （PSO）, and ant colony optimization （ACO） algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.
基金Supported by the National Natural Science Foundation of China under Grant No.50909025
文摘To provide a simulation system platform for designing and debugging a small autonomous underwater vehicle＇s （AUV） motion controller, a six-degree of freedom （6-DOF） dynamic model for AUV controlled by thruster and fins with appendages is examined. Based on the dynamic model, a simulation system for the AUV＇s motion is established. The different kinds of typical motions are simulated to analyze the motion performance and the maneuverability of the AUV. In order to evaluate the influences of appendages on the motion performance of the AUV, simulations of the AUV with and without appendages are performed and compared. The results demonstrate the AUV has good maneuverability with and without appendages.
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 support of Centre of Excellence (CoE) in Complex and Nonlinear dynamical system (CNDS), through TEQIP-II, VJTI, Mumbai, India
文摘Obstacle avoidance becomes a very challenging task for an autonomous underwater vehicle(AUV)in an unknown underwater environment during exploration process.Successful control in such case may be achieved using the model-based classical control techniques like PID and MPC but it required an accurate mathematical model of AUV and may fail due to parametric uncertainties,disturbance,or plant model mismatch.On the other hand,model-free reinforcement learning(RL)algorithm can be designed using actual behavior of AUV plant in an unknown environment and the learned control may not get affected by model uncertainties like a classical control approach.Unlike model-based control model-free RL based controller does not require to manually tune controller with the changing environment.A standard RL based one-step Q-learning based control can be utilized for obstacle avoidance but it has tendency to explore all possible actions at given state which may increase number of collision.Hence a modified Q-learning based control approach is proposed to deal with these problems in unknown environment.Furthermore,function approximation is utilized using neural network(NN)to overcome the continuous states and large statespace problems which arise in RL-based controller design.The proposed modified Q-learning algorithm is validated using MATLAB simulations by comparing it with standard Q-learning algorithm for single obstacle avoidance.Also,the same algorithm is utilized to deal with multiple obstacle avoidance problems.
基金The National Key Research and Development Program(Grant No.2021YFC2801100)Key-area Research and Development Program of Guangdong Province(Grant No.2020B1111010004)Joint Fund of Science&Technology Department of Liaoning Province,State Key Laboratory of Robotics(Grant No.2020-KF-12-05).
文摘A high-efficiency propeller can enable a long mission duration for autonomous underwater vehicles(AUVs).In this study,a new method with OpenProp coupled with computational fluid dynamics was developed to design a propeller for an Explorer100 AUV.The towed system simulation of the AUV was used to measure the nominal wake,and a self-propulsion simulation was used to measure the effective wake at the disc plane just in front of a propeller.Two propellers referring to the nominal wake(propeller 1)and effective wake(propeller 2)were designed with OpenProp and appended with the AUV for self-propulsion simulations,respectively.Through the numerical simulation of the AUV self-propulsion tests,the cruising velocity of AUV was obtained.The flow characteristics of the self-propulsion in pressure and velocity contours were also analyzed.The propeller designed with an effective wake improved the thrust,velocity,and efficiency by approximately 11.3%,6.7%,and 2.5%,respectively,as compared with those with a nominal wake.The cruising velocity of the final designed propeller for the Explorer100 AUV improved by 21.8%,as compared to that of the original propeller from the AUV free-running tests.
文摘Autonomous Underwater Vehicles （AUVs） are capable of conducting various underwater missions and marine tasks over long periods of time. In this study, a novel conflict-free motion-planning framework is introduced. This framework enhances AUV mission performance by completing the maximum number of highest priority tasks in a limited time through a large-scale waypoint cluttered operating field and ensuring safe deployment during the mission. The proposed combinatorial route-path-planner model takes advantage of the Biogeography- Based Optimization （BBO） algorithm to satisfy the objectives of both higher- and lower-level motion planners and guarantee the maximization of mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios, including cost constraints in time-varying operating fields. To demonstrate the reliability of the proposed model, the performance of each motion planner is separately assessed and statistical analysis is conducted to evaluate the total performance of the entire model. The simulation results indicate the stability of the proposed model and the feasibility of its application to real-time experiments.
文摘In view of the characteristics of underwater navigation, the simulation platform of navigation system for autonomous underwater vehicle has been developed based on Windows platform. The system architecture, net communication and the information flow are discussed. The methods of software realization and some key techniques of the Vehicle Computer and the Navigation Equipment Computer are introduced in particular. The software design of Terrain Matching Computer is introduced also. The simulation platform is verified and analyzed through simulation. The results show that the architecture of the platform is reasonable and reliable, and the mathematic models and simulation algorithms of sub-systems are also valid and practicable.
文摘Robust and efficient AUV path planning is a key element for persistence AUV maneuvering in variable underwater environments. To develop such a path planning system, in this study, differential evolution(DE) algorithm is employed. The performance of the DE-based planner in generating time-efficient paths to direct the AUV from its initial conditions to the target of interest is investigated within a complexed 3D underwater environment incorporated with turbulent current vector fields, coastal area,islands, and static/dynamic obstacles. The results of simulations indicate the inherent efficiency of the DE-based path planner as it is capable of extracting feasible areas of a real map to determine the allowed spaces for the vehicle deployment while coping undesired current disturbances, exploiting desirable currents, and avoiding collision boundaries in directing the vehicle to its destination. The results are implementable for a realistic scenario and on-board real AUV as the DE planner satisfies all vehicular and environmental constraints while minimizing the travel time/distance, in a computationally efficient manner.
文摘Up to now, some technology of neural networks are developed to solve the non-linearity of researched objects and to implement the adaptive control in many engineering fields, and some good results were achieved. Though it puts some questions over to design application structure with neural networks, it is really unknowable about the study mechanism of those. But, the importance of study ratio is widely realized by many scientists now, and some methods on the modification of that are provided. The main subject is how to improve the stability and how to increase the convergent rate of networks by defining a good form of the study ratio. Here a new algorithm named LDBP (least disturbance BP algorithm) is proposed to calculate the ratio online according to the output errors, the weights of network and the input values. The algorithm is applied to the control of an autonomous underwater vehicle designed by HEU. The experimental results show that the algorithm has good performance and the controller designed based on it is fine.
文摘A series of experimental studies of the innovative propulsor named Collective and Cyclic Pitch Propeller(CCPP) applied to an underwater vehicle were designed and performed at the Australian Maritime College, University of Tasmania. The bollard pull and captive model tests were conducted to investigate the characteristics of CCPP and to examine the effect of different parameter settings to its performance. The results show that the CCPP is able to generate effective manoeuvring forces in various operational condition. In addition, the obtained results in the form of force coefficients provide a useful empirical model for the simulation and control of an underwater vehicle equipped with this propulsor.
