Numerical computation and analysis of high-speed autonomous underwater vehicle (AUV) moving in head sea based on dynamic mesh

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.

Sonar Image Processing System for an Autonomous Underwater Vehicle(AUV)

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.

深海AUV无动力垂直下潜运动特性研究

深海AUV(自主水下机器人)采用无动力下潜方式能有效节约能源,但是水平或小纵倾角姿态下潜用时较长,水平偏移大。为提高下潜速度,减小下潜偏移距离,对AUV无动力垂直下潜过程进行研究。使用四元数代替欧拉角得到AUV运动方程,并加入洋流和浮力数学模型,通过Simulink仿真模块建立AUV垂直下潜运动仿真方法,解决垂直下潜产生的姿态角解算奇异性问题。通过设置不同仿真工况,得到AUV垂直下潜运动状态量受负浮力、重浮心距离、舵角、初始纵倾角及环境扰动力的作用规律。结果表明,AUV采用垂直下潜方式,可实现较大的下潜速度,同时减小水平偏移距离;洋流扰动是垂直下潜运动产生水平偏移的主要原因;下潜深度6000 m时,浮力变化扰动导致末端下潜速度减小30%,下潜时间增加21%。

面向海流扰动和通信时延的欠驱动AUV编队跟踪控制

由欠驱动自主水下航行器(Autonomous Underwater Vehicle,AUV)编队组成的水下探测阵列具有响应快、机动性好、智能化程度高的特点。针对无速度信息传输的多AUV在海流和时延复合扰动下的编队控制问题,提出一种虚拟轨迹、轨迹预测、自适应反演滑模控制技术相结合的编队控制方法。使用领航者的位置信息和期望队形得到跟随者的参考轨迹,并引入虚拟轨迹使其与跟随者参考轨迹有限时间重合,从而得到跟随者的期望位置和速度。在此基础上,使用最小二乘法拟合轨迹曲线进行时延补偿,并通过自适应反演滑模控制技术完成海流干扰下的编队轨迹跟踪。理论分析和仿真结果表明,新方法具有可行性和有效性。

输入时延与通信时延下AUV集群的牵制控制

针对时延问题对集群稳定性的影响,对牵制控制策略进行研究,利用反馈线性化将水下无人潜航器(AUV)模型简化为二阶积分器模型,研究了具有时延的水下无人潜航器集群下的编队控制问题,并将一致性控制与牵制控制相结合。分析了输入时延和通信时延对水下无人潜航器集群系统的影响,应用Nyquist判据控制理论进行证明,得到了集群中被牵制水下无人潜航器和未被牵制水下无人潜航器组成的系统能渐进收敛达到一致性的充分必要条件。通过数值仿真验证了定理的正确性。

基于粒子群优化-人工势场的多AUV拦截技术研究

在复杂多变的水下环境中,针对港口等环境下的运动入侵目标的拦截问题,提出了一种新的多自主水下机器人(autonomous underwater vehicle,AUV)拦截算法——预测规划拦截法。首先,通过AUV和入侵目标的运动轨迹,依据拦截点思想快速简单地确定拦截位置,对三维环境下拦截点难以计算的问题采用粒子群优化算法选择最优拦截点,有效降低拦截距离。其次,利用人工势场法规划每个AUV在海流环境下的拦截路径。当目标物被环境中任意一个AUV拦截时,则认为拦截成功。仿真结果表明,在存在海流、障碍物的不同水下环境中,预测规划拦截法的拦截效率较传统的跟踪拦截法有较大的提升。

Adaptive Backstepping Terminal Sliding Mode Control Method Based on Recurrent Neural Networks for Autonomous Underwater Vehicle

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.

Bio-inspired geomagnetic navigation method for autonomous underwater vehicle

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.

Consensus of multiple autonomous underwater vehicles with double independent Markovian switching topologies and timevarying delays

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.

Parallel Neural Network-Based Motion Controller for Autonomous Underwater Vehicles

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.

一种AUV模块化载体结构设计与实现

随着科技的不断发展,水下作业任务呈多样化、复杂化的趋势,针对自主式水下无人航行器功能多样性的问题,采用模块化的设计思想,提出一种载体结构设计方法。以某300 m级探测型AUV为例,对本文提出的载体结构进行验证。水池试验结果表明,本文提出的模块化载体结构运行情况良好,保证了AUV各项功能的实现,可为水下无人航行器的工程设计提供参考。

Tracking Control of Autonomous Underwater Vehicles with Internal Moving Mass

追踪轨道的控制问题被调查为一自治在水下作为致动器用一个内部点团和一个后面的推进器搬到垂直飞机的车辆(AUV ) 。与点团的动力学结合了， AUV 作为一个 underactuated 系统被建模。一个基于 Lyapunov 的追踪控制器被使用 backstepping 途径稳定错误动力学并且强迫位置错误到起源的一位小邻居建议。模拟结果验证建议追踪的途径。

A hydrothermal investigation system for the Qianlong-Ⅱ autonomous underwater vehicle

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.

Nonlinear trajectory tracking control of a new autonomous underwater vehicle in complex sea conditions

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.

Reinforcement learning based parameter optimization of active disturbance rejection control for autonomous underwater vehicle

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.

Stability Analysis on Speed Control System of Autonomous Underwater Vehicle

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.

Analysis and innovation of key technologies for autonomous underwater vehicles

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.

Innovative design and motion mechanism analysis for a multi-moving state autonomous underwater vehicles

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.

Identification of Pitch Dynamics of An Autonomous Underwater Vehicle Using Sensor Fusion

This paper presents a method for identification of the hydrodynamic coefficients of the dive plane of an autonomous underwater vehicle. The proposed identification method uses the governing equations of motion to estimate the coefficients of the linear damping, added mass and inertia, cross flow drag and control. Parts of data required by the proposed identification method are not measured by the onboard instruments. Hence, an optimal fusion algorithm is devised which estimates the required data accurately with a high sampling rate. To excite the dive plane dynamics and obtain the required measurements, diving maneuvers should be performed. Hence, a reliable controller with satisfactory performance and stability is needed. A cascaded controller is designed based on the coefficients obtained using a semi-empirical method and its robustness to the uncertainties is verified by the μ-analysis method. The performance and accuracy of the identification and fusion algorithms are investigated through 6-DOF numerical simulations of a realistic autonomous underwater vehicle.