水下自主机器人水动力预报方法研究

针对水下机器人操纵性优化设计中水动力系数预报问题,在水下机器人水动力预报中引入艇体肥瘦指数概念,确定了水下机器人艇体几何描述的五参数模型。提出采用小波神经网络方法预报水下机器人水动力,确定了神经网络的结构,利用均匀试验设计方法,设计了神经网络的学习样本。研究结果表明,只要确定适当的输入参数,选择适当的学习样本和网络结构,利用小波神经网络方法对水下机器人水动力进行预报可以达到较好的精度。     

Neural Network Based Robust Controller for Trajectory Tracking of Underwater Vehicles

A robust neural network controller (NNC) is presented for tracking control of underwater vehicles with uncertainties. The controller is obtained by using backstepping technique and Lyapunov function design in combination with neural network identification. Modeling errors and environmental disturbances are considered in the mathematical model. A two-layer neural network is introduced to compensate the modeling errors, while H∞ control strategy is used to achieve the L2-gain performance. The uniformly ultimately bounded (UUB) stabilities of tracking errors and NN weights are guaranteed through the proposed controller. An on-line NN weights tuning algorithm is also proposed. Good performances of the tracking control system are illustrated by the results of numerical simulations.     

自主水下航行器的软变结构控制

研究自主水下航行器系统的软变结构控制策略问题。首先分析软变结构控制系统的结构特征,利用双曲正切函数,给出控制受限情形的软变结构控制策略。其次利用Lyapunov稳定性理论,讨论自主水下航行器软变结构控制系统的稳定性,然后构造了基于双曲正切函数的软变结构控制器,给出自主水下航行器软变结构控制的具体算法。基于双曲正切函数的自主水下航行器软变结构控制系统调节精度高,响应速度快,有效地削弱了系统抖振。最后通过一个仿真实验,比较了自主水下航行器垂直深度通道的4种控制策略对系统性能的影响,从而验证了研究方法的有效性。     

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.     

水下滑翔器主体外形优化设计

对水下滑翔器主体外形的优化设计问题进行研究.首先,在考虑内部机械结构限制的条件下,建立了主体外形优化数学模型,并采用CFX计算了若干主体形状的绕流阻力.在此基础上建立了映射主体外形的尺寸参数与绕流阻力的BP神经网络.然后将建立的神经网络作为优化设计问题的目标函数,采用坐标轮换法对滑翔器主体外形进行了优化设计,确定了尺寸参数的最优解.     

小型水下自航行平台控制体系开发

以小型、经济、易扩展为目标,采用模块化设计思想,开发了一种基于CAN总线的递阶一分布式水下自航行平台控制系统,并重点考虑了安全可靠性,对各节点负载进行了优化分配。实际应用表明,该控制系统结构简单、性能可靠、传输率高,能够满足平台工作环境复杂多变的要求。     

AUV自主导航航位推算算法的分析研究

地球形状的不规则性,各种导航传感器本身的误差,以及仪器的安装偏差等,使得AUV(自治水下机器人)在进行远距离自主航行时,自主导航的精度大大下降。针对以上问题及实际工程需要,论文对AUV自主导航的航位推算算法做了进一步研究并加以改进,以提高其自主导航精度。最后,利用2004年中国科学院沈阳自动化所水下机器人研究中心进行AUV湖试所获得的数据,对文中提出的算法进行了验证。结果表明,AUV的自主导航精度得到大大提高,可以用于修正原来的自主导航算法。     

面向海洋观测的长续航力移动自主观测平台发展现状与展望

南海拥有丰富的渔业资源,其中南海中南部大洋性、上升流区域更是具有很大的开发潜力和商业价值.西沙群岛位于南海中部,是我国海南省三沙市的重要组成部分之一.西沙群岛及其附近海域气候条件优越,拥有丰富的海洋渔业、海洋植被和油气矿藏等海洋资源,其中又以渔业资源的开发潜力最大.在南海问题近年来显著升温的背景下,通过推动加大南海特别是西沙海域的渔业资源开发力度,妥善处理南海争议、更好地维护我国南海主权权益,具有重要的现实意义和深远影响.     

基于CAN总线的水下机器人执行节点设计与实现

文中提出了一种基于CAN总线的水下机器人分布式控制系统结构,主要设计其执行节点,包括P87C591单片机为核心的的硬件电路和软件结构设计。     

水下滑翔器整体外形设计及水动力性能分析

对水下滑翔器的整体外形设计与水动力性能进行研究。在Slocum等几种典型水下滑翔器样机的基础上,对滑翔器的主体和附体进行一体化设计,得到阻力最小的新型水下滑翔器构型设计。利用CFD方法对水下滑翔器进行模拟仿真,通过分析对比五种主体构型,得到了比较合理的主体线型,然后用正交设计方法和曲线拟合法对附体进行了优选工作,最后得到了性能更优的整体载体外形。模拟仿真实验表明,滑翔器在8°左右攻角航行时,具有最大的升阻比;和Slocum等经典样机相比,新的载体具有更好的水动力性能。通过上述研究工作,也可以缩短水下滑翔器研制周期,降低设计成本,并为水下滑翔器的更优设计提供了有力的技术指导和参考。     

Development of A Three-Dimensional Guidance System for Long-Range Maneuvering of A Miniature Autonomous Underwater Vehicle

The present paper introduces a three-dimensional guidance system developed for a miniature Autonomous Underwater Vehicle（AUV）. The guidance system determines the best trajectory for the vehicle based on target behavior and vehicle capabilities. The dynamic model of this novel AUV is derived based on its special characteristics such as the horizontal posture and the independent diving mechanism. To design the guidance strategy, the main idea is to select the desired depth, presumed proportional to the horizontal distance of the AUV and the target. By connecting the two with a straight line, this strategy helps the AUV move in a trajectory sufficiently close to this line. The adjacency of the trajectory to the line leads to reasonably short travelling distances and avoids unsafe areas. Autopilots are designed using sliding mode controller. Two different engagement geometries are considered to evaluate the strategy＇s performance： stationary target and moving target. The simulation results show that the strategy can provide sufficiently fast and smooth trajectories in both target situations.     

混合驱动自主潜航器续航能力分析

混合驱动自主潜航器融合了自主潜航器机动灵活和水下滑翔机续航能力强的优点,针对自身携带能源有限的问题,对在两种工作模式下如何实现最大航行距离进行了研究.从航行过程中的能源消耗入手,得出航行距离与速度、电子设备功率等的关系,通过理论分析和仿真手段得出最大续航能力的实现方法.在螺旋桨驱动模式下,当以经济航速航行时,可以达到最大航行距离;在浮力驱动模式下,当以最大滑翔效率航行时,水平方向上的滑翔距离最大,并且水平方向上的滑翔距离随着剖面深度的增大而增大,当剖面深度大到一定程度之后,最大滑翔距离趋于恒定.该研究方法可为类似水下航行器电源管理系统的能源分配提供参考,也可为航行器外形的设计和传感器的选型提供理论指导.     

Parallel trajectory planning for shipborne Autonomous collision avoidance system

Collision at sea is always a significant issue affecting the safety of ship navigation. The shipborne autonomous collision avoidance system (SACAS) has the great advantage to minimize collision accidents in ship navigation. A parallel trajectory planning architecture is proposed in this paper for SACAS system. The fully-coupled deliberative planner based on the modified RRT algorithm is developed to search for optimal global trajectory in a low re-planning frequency. The fully-coupled reactive planner based on the modified DW algorithm is developed to generate the optimal local trajectory in a high re-planning frequency to counteract the unexpected behavior of dynamic obstacles in the vicinity of the vessel. The obstacle constraints, ship maneuvering constraints, COLREGs rules, trajectory optimality, and real-time requirements are satisfied simultaneously in both global and local planning to ensure the collision-free optimal navigation in compliance with COLREGs rules. The on-water tests of a trimaran model equipped with a model-scale SACAS system are presented to demonstrate the effectiveness and efficiency of the proposed algorithm. The good balance between the computational efficiency and trajectory optimality is achieved in parallel trajectory planning.     

基于水下自主航行器（AUV）的神狐峡谷谷底块体搬运沉积特征及其对深水峡谷物质输运过程的指示

海底峡谷是陆源物质向深海运移的重要通道。对于远离陆地的海底峡谷,通常认为浊流是物质搬运的主要营力。受限于探测精度和复杂作业环境影响,使用常规地球物理资料对深水海底峡谷尤其是对谷底沉积体的形态和结构特征的刻画不够精细。基于水下自主航行器（AUV, Autonomous Underwater Vehicle）采集的高分辨率多波束、旁扫声呐和浅地层剖面资料,对神狐峡谷群中的一条峡谷的谷底表面及部分浅部地层的沉积特征进行了分析。结果表明,峡谷谷底浅部地层并不像它平滑的表面那么简单,而是由大量内部杂乱弱反射、厚度在8.4 m及以下的块体搬运沉积体组成。峡谷中下游块体搬运沉积体大都沿峡谷走向整体呈条带状展布,不是直接来源于相邻的峡谷脊部。研究认为在特定沉积环境下（例如高海平面时期）,陆坡限定性峡谷谷底的块体搬运沉积过程的重复进行是峡谷谷底物质输运的重要途径,与浊流共同雕刻了峡谷的地形地貌。基于AUV的地球物理探测技术将是研究海底浅表层沉积过程和保障海底工程施工的重要手段。     

An Advanced Probabilistic Neural Network for the Design of Breakwater Armor Blocks

In this study,an advanced probabilistic neural network(APNN)method is proposed to reflect the global probability density function(PDF)by summing up the heterogeneous local PDF which is automatically determined in the individual standard deviation of variables.The APNN is applied to predict the stability number of armor blocks of breakwaters using the experimental data of van der Meer,and the estimated results of the APNN are compared with those of an empirical formula and a previous artificial neural network(ANN)model.The APNN shows better results in predicting the stability number of armor blocks of breakwater and it provided the promising probabilistic viewpoints by using the individual standard deviation in a variable.     

Closed-loop randomized kinodynamic path planning for an autonomous underwater vehicle

A randomized kinodynamic path planning algorithm based on the incremental sampling-based method is proposed here as the state-of-the-art in this field applicable in an autonomous underwater vehicle. Designing a feasible path for this vehicle from an initial position and velocity to a target position and velocity in three-dimensional spaces by considering the kinematic constraints such as obstacles avoidance and dynamic constraints such as hard bounds and non-holonomic characteristic of AUV are the main motivation of this research. For this purpose, a closed-loop rapidly-exploring random tree (CL-RRT) algorithm is presented. This CL-RRT consists of three tightly coupled components: a RRT algorithm, three fuzzy proportional-derivative controllers for heading and diving control and a six degree-of-freedom nonlinear AUV model. The branches of CL-RRT are expanded in the configuration space by considering the kinodynamic constraints of AUV. The feasibility of each branch and random offspring vertex in the CL-RRT is checked against the mentioned constraints of AUV. Next, if the planned branch is feasible by the AUV, then the control signals and related vertex are recorded through the path planner to design the final path. This proposed algorithm is implemented on a single board computer (SBC) through the xPC Target and then four test-cases are designed in 3D space. The results of the processor-in-the-loop tests are compared by the conventional RRT and indicate that the proposed CL-RRT not only in a rapid manner plans an initial path, but also the planned path is feasible by the AUV.