基于Adams与Matlab/Simulink的水下自航行器协同仿真

针对传统水下自航行器(Autonomous underwater vehicle,AUV)仿真中图形界面、实时性和动力学性能难以兼顾的问题,提出利用虚拟样机分析软件Adams和控制仿真软件Matlab/Simulink联合建立AUV虚拟样机系统的方法。在分析虚拟样机系统运动学、动力学和水动力数学模型的基础上,给出虚拟样机物理模型及控制模型的建立过程,并利用该虚拟样机系统对设计的AUV空间动态定位控制算法进行基于动力学基础的仿真分析。仿真试验的过程及结果表明,该虚拟样机系统具备智能控制与动态控制交互仿真演示和功能验证的能力,可为AUV图形仿真研究提供一种新的解决思路,对研究水下自航行器的操纵与控制有重要的现实意义。

小型水下自航行器动力学建模与控制

水下自航行器动力学建模是其控制研究的基础,为此基于Newton Euler法建立了水下自航行器的一般动力学模型,其模型具有复杂非线性特征.利用解耦和摄动理论对模型进行了合理简化,将控制系统分解为弱耦合的子系统.基于简化模型设计了航速、航向、纵倾和深度控制器,仿真结果证明了自航行控制的鲁棒性和稳定性.

基于模糊控制的水下自航行器着陆策略分析

由于所携带能源总量的限制,目前水下自航行器(Autonomous underwater vehicle,AUV)不能满足长时间海洋环境测量的要求。为了有效地减少能耗,解决AUV工作时间短的问题,提出一种具有变浮力系统、能够着陆坐底的小型AUV。该AUV通过着陆坐底实现定点测量,可以利用有限的能源实现长时间的海洋环境监测。基于此,对AUV的着陆策略进行研究。在对注水自由下沉着陆策略进行分析的基础上,分析水舱注水量与着陆速度、着陆时间以及着陆俯仰角的关系。最终选择控制注水着陆策略作为AUV的水下着陆方案,并基于模糊控制设计着陆控制器。该方法根据AUV距离海底的高度和俯仰角通过模糊推理来控制AUV水舱的注水量,可以使AUV以较短的时间着陆于海底,同时又将着陆速度和着陆俯仰角控制在很小的范围内,满足了AUV安全着陆的要求。仿真和水域试验结果证明了采用该着陆策略的可行性。

小型水下自航行器自沉浮装置设计与研究

文中对水下自航行器(Autonomous Underwater Vehicle,简称AUV)的自沉浮装置进行了详细设计与研究。通过对已有的自沉浮装置方案进行对比研究,设计了以高压气体吹除压载水舱的新型自沉浮装置,该装置具有结构简单、可靠性高和可维护性好的特点,并可实现模块化设计。最后,对装置的主要设计参数进行了计算与优化。

水下自航行器外形及水动力性能优化

研究水下自航行器(AUV)外形及水动力性能优化的问题,为使得AUV具有较小航行阻力的同时拥有较大承载能力,需要不断进行AUV模型重建以及水动力结果分析,人工完成将会耗时很长,Isight多学科优化设计平台搭载常用的优化算法—NSGA-II遗传算法,整合Solidworks、Gambit、Fluent三大集成模块实现数据交换以进行AUV外形的建模、仿真并完成设计过程的自动化和智能的设计探索,确定最佳设计参数;仿真结果表明,最终优化后的AUV不仅减小了航行阻力并且拥有更大的承载能力;因此采用多学科优化软件Isight能够有效提高AUV外形及水动力性能优化的准确性和效率,提升其整体水动力性能。

水下自航行器近海底处水动力性能分析

由于海底边界效应和复杂多变地形的影响,对水下自航行器(autonomous underwater vehicle,AUV)的运行稳定性和操纵性提出了更高要求,本文针对近海底处AUV的水动力性能进行了建模与分析,预测并控制AUV在近海底处的运动。利用计算流体力学方法和ANSYS ICEM软件对近海底处的AUV进行六面体结构网格划分,然后利用Fluent对近海底流场进行数值模拟仿真和分析,结合仿真结果分析了距海底的距离、航行速度、攻角、前方下面斜坡倾角大小和斜坡水平长度对水下自航行器特性的影响。结果表明,在距海底1500mm时,海底壁面就几乎不再影响AUV的水动力性能;攻角为0°航行时,AUV会受到向下的力;随着前方下面的斜坡倾角大小和斜坡水平长度的增加,其阻力系数减小。

混合驱动水下自航行器控制系统设计

将32位ARM微处理器应用于混合驱动水下自航行器的控制系统。首先介绍了混合驱动AUV控制系统的总体体系结构,将CAN总线应用于混合驱动AUV,开发了基于CAN总线的分布式控制系统;简单介绍了以ARM7微处理器LPC2129为主控制芯片的控制系统硬件设计;制定了适用于混合驱动AUV的CAN应用层协议和相应的软件,遵照分层递阶的体系结构设计了控制系统的软件,并采取软硬件相结合的方法解决了控制系统的可靠性问题。联调实验证明该系统性能稳定、工作可靠。

基于IAP的水下自航行器在线编程设计

为了解决水下自航行器的程序升级问题,将核心芯片LPC2138的片内Flash划分为3个区,分别存放Bootloader、程序运行标志及主程序。Bootloader在运行过程中接收新的程序代码,应用IAP技术将其编程至Flash,并更新程序运行标志,编程完毕后,跳转到相应的位置运行。为了增加系统的可靠性,综合运用看门狗和程序运行标志,使系统在异常情况下也能正常运行。

基于LPC2292的通用型水下机器人控制系统设计

分析了混合驱动水下自航行器的优势,简述了天津大学开发的Petre1要完成的功能任务。在充分考虑可移植性的基础上,设计了堆码结构的控制系统硬件,并介绍了控制系统的软件结构以及在线编程功能的软件实现。

基于双闭环的矢量推进器的AUV转向控制方法

水下无人自航行器(autonomous underwater vehicle,AUV)在对海洋环境进行勘查与测量时,实际航迹与目标航迹的偏差要求控制在一定精度范围内.在传统常采用的航向单闭环方法控制下,基于矢量推进器的AUV在高速转向时存在航迹跟踪效果差的缺点.针对这一问题,设计了一种双闭环自适应转向运动控制方法.该方法基于矢量推进器机动性强的特性,在AUV转向时将航向控制闭环和航速控制闭环设计成双闭环,调整航向的同时依据航向环偏航角差实时控制航速环AUV转向目标速度.理论分析和实验证明:在AUV转向时,该控制算法可以更好地实现航迹跟踪,实际航行轨迹与目标航迹的最大偏差可以控制在10,m以内.

Application of unscented Kalman filter to novel terrain passive integrated navigation system

To improve the navigation accuracy of an autonomous underwater vehicle （AUV）, a novel terrain passive integrated navigation system （TPINS） is presented. According to the characteristics of the underwater environment and AUV navigation requirements of low cost and high accuracy, a novel TPINS is designed with a configuration of the strapdown inertial navigation system （SINS）, the terrain reference navigation system （TRNS）, the Doppler velocity sonar （DVS）, the magnetic compass and the navigation computer utilizing the unscented Kalman filter （UKF） to fuse the navigation information from various navigation sensors. Linear filter equations for the extended Kalman filter （EKF）, nonlinear filter equations for the UKF and measurement equations of navigation sensors are addressed. It is indicated from the comparable simulation experiments of the EKF and the UKF that AUV navigation precision is improved substantially with the proposed sensors and the UKF when compared to the EKF. The TPINS designed with the proposed sensors and the UKF is effective in reducing AUV navigation position errors and improving the stability and precision of the AUV underwater integrated navigation.

Actuator fault diagnosis of autonomous underwater vehicle based on improved Elman neural network

Autonomous underwater vehicles(AUV) work in a complex marine environment. Its system reliability and autonomous fault diagnosis are particularly important and can provide the basis for underwater vehicles to take corresponding security policy in a failure. Aiming at the characteristics of the underwater vehicle which has uncertain system and modeling difficulty, an improved Elman neural network is introduced which is applied to the underwater vehicle motion modeling. Through designing self-feedback connection with fixed gain in the unit connection as well as increasing the feedback of the output layer node, improved Elman network has faster convergence speed and generalization ability. This method for high-order nonlinear system has stronger identification ability. Firstly, the residual is calculated by comparing the output of the underwater vehicle model(estimation in the motion state) with the actual measured values. Secondly, characteristics of the residual are analyzed on the basis of fault judging criteria. Finally, actuator fault diagnosis of the autonomous underwater vehicle is carried out. The results of the simulation experiment show that the method is effective.

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.

Application of GA, PSO, and ACO Algorithms to Path Planning of Autonomous Underwater Vehicles

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.

H_∞ Robust Fault-Tolerant Controller Design for an Autonomous Underwater Vehicle’s Navigation Control System

In order to improve the security and reliability for autonomous underwater vehicle （AUV） navigation, an H∞ robust fault-tolerant controller was designed after analyzing variations in state-feedback gain Operating conditions and the design method were then analyzed so that the control problem could be expressed as a mathematical optimization problem. This permitted the use of linear matrix inequalities （LMI） to solve for the Hv controller for the system. When considering different actuator failures, these conditions were then also mathematically expressed, allowing the H∞ robust controller to solve for these events and thus be fault-tolerant. Finally, simulation results showed that the H∞ robust fault-tolerant controller could provide precise AUV navigation control with strong robustness.

Dynamic formation control for autonomous underwater vehicles

Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles(AUVs) to collaborate with each other.In this work,a dynamic formation model was proposed,in which several algorithms were developed for the complex underwater environment.Dimension changeable particle swarm algorithm was used to find an optimized path by dynamically adjusting the number and the distribution of the path nodes.Position relationship based obstacle avoidance algorithm was designed to detour along the edges of obstacles.Virtual potential point based formation-keeping algorithm was employed by incorporating dynamic strategies which were decided by the current states of the formation.The virtual potential point was used to keep the formation structure when the AUV or the formation was deviated.Simulation results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness,even with a concave obstacle.It has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.

Three-dimensional neural network tracking control of autonomous underwater vehicles with input saturation

This paper addresses the problem of three-dimensional trajectory tracking control for underactuated autonomous underwater vehicles in the presence of parametric uncertainties,environmental disturbances and input saturation.First,a virtual guidance control strategy is established on the basis of tracking error kinematics,which resolves the overall control system into two cascade subsystems.Then,a first-order sliding mode differentiator is introduced in the derivation to avoid tedious analytic calculation,and a Gaussian error function-based continuous differentiable symmetric saturation model is explored to tackle the issue of input saturation.Combined with backstepping design techniques,the neural network control method and an adaptive control approach are used to estimate composite items of the unknown uncertainty and approximation errors.Meanwhile,Lyapunov-based stability analysis guarantees that control error signals of the closed-loop system are uniformly ultimately bounded.Finally,simulation studies are conducted for the trajectory tracking of a moving target and a spiral line to validate the effectiveness of the proposed controller.

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.

A Potential Flow Based Flight Simulator for an Underwater Glider

Underwater gliders are recent innovative types of autonomous underwater vehicles （AUVs） used in ocean exploration and observation. They adjust their buoyancy to dive and to return to the ocean surface. During the change of altitude, they use the hydrodynamic forces developed by their wings to move forward. Their flights are controlled by changing the position of their centers of gravity and their buoyancy to adjust their trim and heel angles. For better flight control, the understanding of the hydrodynamic behavior and the flight mechanics of the underwater glider is necessary. A 6-DOF motion simulator is coupled with an unsteady potential flow model for this purpose. In some specific cases, the numerical study demonstrates that an inappropriate stabilizer dimension can cause counter-steering behavior. The simulator can be used to improve the automatic flight control. It can also be used for the hydrodynamic design optimization of the devices.

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 environnaent.