Design and evaluation of a hierarchical control architecture for an autonomous underwater vehicle

This paper researches on a kind of control architecture for autonomous undelwater vehicle （AUV）. After describing the hybrid property of the AUV control system, we present the hierarchical AUV control architecture. The architecture is organized in three layers： mission layer, task layer and execution layer. State supervisor and task coordinator are two key modules handling discrete events, so we describe these two modules in detail. Finally, we carried out a series of tests to verify this architecture The test results show that the AUV can perform autonomous missions effectively and safely. We can conclude the control architecture is valid and practical.     

Expert S-surface control for autonomous underwater vehicles

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.     

S~2 BHCA-Multiple AUVs cooperation oriented control architecture

Oceanographic survey, or other similar applications should be the applications of multiple AUVs. In this paper, the skill & simulation based hybrid control architecture (S2BHCA) as the controller's design reference was proposed. It is a multi-robot cooperation oriented intelligent control architecture based on hybrid ideas. The S BHCA attempts to incorporate the virtues of the reactive controller and of the deliberative controller by introducing the concept of the "skill". The additional online task simulation ability for cooperation is supported, too. As an application, a multiple AUV control system was developed with three "skills" for the MCM mission including two different cooperative tasks. The simulation and the sea trials show that simple task expression, fast reaction and better cooperation support can be achieved by realizing the AUV controller based on the S2BHCA.     

Market based framework for multiple AUVs cooperation

A“Market” based framework for multiple AUVs team is introduced in this paper. It is a distributed meta-level task allocation framwork. The formulation and the basic concepts of the “Market” such as “goods” and “price” are discussed first, then the basic algorithm of the “auction”. The loosely coupled v-MDTSP tasks are considered as an example of the task allocation mission. A multiple AUV team controller and a detailed algorithm are developed for such applications. The simulation results show that the controller has the advantages such as robustness and low complexity and it can achieve better optimization results than the classical central controller （ such as GA） in some tasks. And the comparison of two different local solvers also implies that we should get the reasonable task allocation even not using the high quality algorithm, which can considerably decrease the cooperation computation.     

自主水下航行器发展概述

自主水下航行器（AUVs）因其应用于海洋勘探而逐渐成为一个有趣的研究对象。波浪滑翔机是一种行驶于波浪表面的无人滑行器（SUV）,它借助海洋能来推动自己,这对于典型的AUVs所采用的电机供能以及昂贵的锚链系统浮标供
　　能来说,是一种技术上的重大跨越。该文讨论了最有效率的AUVs类型。第一部分为每一种类型的发展历程,第二部分为它们各自的技术特点。此外,波浪滑翔机作为应用于海洋部门的一种新型水下机器人,文中简要地给出它的过去,现在以及未来的发展概述。研究波浪滑翔机的意义在于证明它的效率以及实用性,进而取代诸多的AUVs来实现各种实际应用。而研究结果也表明波浪滑翔机确实可以应用于众多领域。对于海洋检测而言,相比于其他AUVs,波浪滑翔机提供了更廉价,更经济,更环保的作业模式,同时也不需要缆绳、船舶等海上作业服务。     

近壁面水动力干扰下的AUV运动控制研究

按自治式水下机器人(AUV)需要接近水下工作站并实现坐落的要求,依据平壁面对AUV水动力干扰的力学机理,建立了AUV在平壁面附近运动时的数学模型,并设计了五个自由度运动PID控制器.在海流影响下,通过系统仿真,实现了AUV的五自由度运动控制和准确坐落,仿真结果验证了控制策略的可行性.     

水下无人作战系统装备现状及发展趋势

海军水下无人作战系统因其造价低廉、隐蔽性强、避免人员伤亡等诸多优点而得到大力发展,美国等国已制定各类水下无人作战系统发展规划并开发出便携型、轻型、重型和巨型等多种水下无人作战系统,并向着提高智能化、模块化和标准化程度、拓展多平台搭载使用能力等方向发展。为了应对威胁,我国也应从顶层规划水下无人作战体系发展路线,开发多样化的水下无人作战系统。     

水下航行器三维航迹反演滑模跟踪控制

  目的  旨在研究非线性六自由度自主水下航行器（AUV）的轨迹跟踪问题。  方法  为此,设计三维轨迹变前视距离视线（LOS）导引律,利用李雅普诺夫稳定性判据证明此导引律的稳定性,使用设计的自适应S面控制算法对AUV的航向角、纵倾角和纵向速度进行控制。然后,以REMUS 100 AUV为例, 利用Matlab软件分别对AUV的航向角、纵倾角和纵向速度控制及其空间直线、曲线轨迹跟踪进行仿真,以验证所提导引律的有效性。  结果  结果表明：对于非线性控制而言,相比于传统的S面控制,自适应S面控制可降低控制参数整定的难度,抗干扰能力更强;而且,相比于传统的LOS导引律,所提导引律可使AUV更快地跟踪上参考轨迹。  结论  所设计的轨迹跟踪控制算法能够实现对AUV的三维轨迹跟踪,并改善AUV的操纵性。     

拍动式仿鹞鲼水下机器人设计及其游动性能试验

  目的  自然界中的鱼类经过长期的自然选择过程,进化出了各具特色的水中推进模式,具有推进效率高、机动性强与噪音低等优点,是水下航行器的理想仿生对象。为研制新一代低噪声、高机动性的自主水下航行器(AUV),以拍动推进的鹞鲼为仿生对象。  方法  通过分析其胸鳍内在的解剖结构,提出了一种采用对侧柔性胸鳍拍动推进的仿生机器人设计方案,并详述了实验样机本体的制作过程及其底层驱动控制方法。为测试机器鱼样机的游动性能,在实验水域中对所设计的原型样机展开了一系列游动性能测试。实验中测试了机器鱼样机在不同拍动频率下的游动速度,并在确定最大游动速度后,对其进行了机动性能测试。  结果  结果表明,所设计的实验样机能在水中完成包括翻滚、小半径转向与横滚盘旋在内的多种机动动作,其最大游动速度可达1.9倍体长每秒(约为0.73m/s)。  结论  研究初步完成了拍动式仿鹞鲼水下机器人的设计与测试工作,为新一代高性能水下推进器的设计提供了一定的参考价值。     

基于对偶四元数法的AUV运动仿真

本文应用对偶四元数法(Dual Quaternions)建立AUV六自由度运动学和动力学方程,然后运用数值积分对所建模型进行仿真.对偶四元数是对偶数与四元数在多维空间中的有机结合,它继承了四元数与对偶数的优点,可以在三维空间中统一表示刚体的旋转与平移,并且没有常规欧拉法存在的姿态奇异性问题.仿真结果表明,对偶四元数法表达形式简单而统一,特别适用于具有大姿态角度运动的AUV运动仿真.     

积分变结构控制原理在AUV航向控制中的应用仿真

文章研究了积分变结构控制在自主水下机器人(AUV)航向控制系统中的应用,建立了AUV水平面的非线性模型,并在特定的工作点对模型进行了线性化处理,得到了AUV的控制设计线性模型.根据变结构控制理论设计了积分变结构控制器,并给出了消除抖振的方法.仿真试验验证了该设计方法的有效性.     

欠驱动自主水下航行器的镇定及跟踪

针对仅带有轴向推力及偏航力矩的欠驱动自主水下航行器（AUV）,研究了其在水平面内的轨迹跟踪及定点调节问题。基于Lyapunov直接法及串接一反步技术,通过采用一种带有动力学震荡器的跟踪误差变换,设计了一种统一的连续时变状态反馈控制律,并给出了参数自适应更新律以估计AUV的非线性阻力参数,使得AUV的位置及方向角的跟踪误差全局渐近收敛于零点左右的一个邻域内,该区域可以为任意小,并且,AUV的跟踪性能与外界干扰的大小无关。仿真结果证明所提出的方法是有效的。