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题名: 基于多水下机器人编队的化学羽流探测研究
其他题名: Research on Chemical Plume Exploration via Multiple AUVs with Formation-Keeping
作者: 康小东
导师: 封锡盛 ; 李一平
分类号: TP242
关键词: 多AUV系统 ; 协作化学羽流探测 ; 群体AUV控制体系结构 ; 协调协作机制 ; 主-从AUV编队控制
索取号: TP242/K26/2010
学位专业: 模式识别与智能系统
学位类别: 博士
答辩日期: 2010-11-28
授予单位: 中国科学院沈阳自动化研究所
学位授予地点: 中国科学院沈阳自动化研究所
作者部门: 水下机器人技术研究室
中文摘要: 本文在国家863计划的支持下,以深海热液羽流探测为背景,基于仿生学和群体智能的理论框架,研究适合多AUV协作化学羽流探测使命的群体AUV控制体系结构、协调协作机制、三维队形控制方法、协作化学羽流跟踪方法和羽流源定位算法。具体研究内容及研究结论可概述为如下几个方面: 1、对基于仿飞蛾行为策略的单体AUV化学羽流探测进行了改进性研究。主要包括四个方面:①对羽流搜索和羽流维持行为的参数进行了优化;②针对羽流重拾行为所特有的三叶草轨迹,设计了路径跟踪控制器,通过有无海流扰动下的仿真实验验证了路径跟踪控制器的有效性和鲁棒性;③在Wei Li等[67]建立的羽流模型的基础上,基于优化后的行为参数和载体参数开发了单体AUV化学羽流探测仿真系统;④在单体AUV化学羽流探测仿真系统上实现了两种羽流源定位算法:SIZ_T和SIZ_F算法,连续1000次的蒙特卡洛仿真实验验证了这两种定位算法的有效性,以及SIZ_F算法较于SIZ_T算法的优越性。 2、提出一种混合分层的AUV控制体系结构,以及一种基于个性概念和拍卖方法相结合的多AUV协作策略:PACS策略。有、无协作多AUV化学羽流探测的连续1000次蒙特卡洛仿真对比实验验证了混合分层的AUV控制体系结构和PACS策略在仿真条件下的有效性。 3、利用跟随领航者法对多AUV三维编队控制进行了深入研究,包括:①为减小从AUV动力学特性下的速度跟踪误差设计了速度跟踪补偿器;②结合载体动力学特性设计了主-从AUV编队系统的鲁棒控制器;③将队形反馈信息引入到主AUV的轨迹跟踪控制器中,设计了主-从AUV协调编队的辅助控制律;④运用Lyapunov理论证明了主-从AUV之间的编队跟踪误差和从AUV的速度跟踪误差都可以收敛到零,整体系统渐进稳定。MATLAB仿真系统的实验结果验证了主-从AUV编队鲁棒控制器和编队协调控制器的有效性。 4、在单体AUV羽流探测行为参数优化、群体AUV控制体系结构和三维编队控制方法研究的基础上,重点研究了多AUV协作化学羽流跟踪方法。研究的内容包括:①将主-从AUV编队控制映射为从AUV的队形保持行为,设计了主、从AUV自适应行为规划器,主、从AUV依据PACS策略进行角色和行为的动态切换;②针对羽流环境和多AUV协作化学羽流跟踪的使命特点,对队形保持行为参数进行了优化并对羽流宽度进行了估计;③针对严格队形和松散队形两种群体AUV队形配置对三叶草路径进行跟踪研究,设计了主-从AUV编队路径跟踪控制系统,对羽流重拾行为重新进行设计并对其行为参数进行了优化;④依据优化后的行为参数开发了多AUV协作化学羽流探测仿真系统,并用大量蒙特卡洛仿真实验验证了研究内容在仿真条件下的有效性。 5、针对复杂动态的羽流环境、水下弱通信条件以及羽流的时空分布特性,基于单体AUV化学羽流源定位算法提出了两种多AUV协作羽流源定位算法:C_SIZ_T和C_SIZ_F算法。多AUV协作化学羽流探测仿真系统上的连续1000次蒙特卡洛仿真实验验证了这两种定位算法在仿真条件下的有效性,性能对比实验验证了协作多AUV较于单体AUV在羽流探测方面的优越性。 此外,本文还充分利用小型ROV载体开展了虚实相结合的水池和海上试验研究。其中,实际的载体在水池或海上按照羽流跟踪策略航行,虚拟的羽流和海流信息由单体AUV化学羽流探测仿真系统提供。本文在水池验证了10×10米尺度、在海上验证了100×100米尺度下单体AUV羽流探测方法的有效性。 综上,本文以理论探索和仿真实验相结合的研究方式,对多AUV协作化学羽流探测方法进行了全面系统的研究,涵盖了羽流探测过程中从搜索、到跟踪、以至最终定位源头的全过程,为未来基于多AUV系统的羽流探测应用提供了一种可行性方案、奠定了理论基础。
英文摘要: Under the support of Chinese National 863 Plan Program, and based on the theoretical framework of bionics and swarm intelligence, this thesis uses the collaborated multi-AUV system which carries a single chemical sensor as a researching background, studies the control architectures of swarm AUVs, the coordination and cooperation mechanisms, three-dimensional formation control methods, cooperative CPT approaches, the plume source identification algorithms, and so on to meet the requirements of collaborated CPE that with multiple AUVs. And the main contents and researching conclusions of this thesis are summarized as follows. 1. Performing improved researching works for the CPE missions that via a single AUV based on the moth-inspired behavioral strategies developed by Wei Li, et al. The researching works include the following four aspects. ①We optimize the behavioral parameters for the Find-Plume behavior and Maintain-Plume behavior using Monte Carlo simulation approach. ②We design a path following controller to track the cloverleaf trajectory for the Reacquire-Plume behavior. Simulation results with and without current disturbances verify the effectiveness and robustness of the proposed path following controller. We achieve the Reacquire-Plume behavior and optimize its behavioral parameters. ③We develop a simulation system for the CPE via a single AUV, which based on the plume model that developed by Wei Li et al, the optimized behavioral parameters and the vehicle’s parameters. ④We implement two source identification algorithms of SIZ_T and SIZ_F that developed by Wei Li in the CPE simulation system. We keep changing the chemical plume in a fluid environment over 130 hours and perform 1000 CPT test runs for both algorithms. Simulation results show the effectiveness of these two source identification algorithms. Then we make comparisons between the simulation results obtained from this thesis and the results proposed by Wei Li in his literature. Then we can draw a conclusion that the SIZ_F algorithm is superior to SIZ_T algorithm, and the CPT performance in this thesis has been improved significantly. 2. We propose a kind of hybrid hierarchical control architecture and a cooperation strategy of PACS (Personality and Auction Cooperation Strategy) that combining the personality concept of psychology with the auction method in market mechanism for the multi-AUV system. 1000 test runs are performed for the CPE via multiple AUVs that with and without cooperation, respectively, and a comparison about their performances is made, accordingly. Simulation results validate the effectiveness of the proposed hybrid hierarchical architecture and PACS cooperation strategy. 3. Based on the leader-follower method, we study the formation control in 3 dimensions for the multi-AUV system thoroughly and obtain the achievements in three aspects. ①We design a speed tracking compensator for the follower AUVs to solve the speed tracking errors in dynamics. ②Combining the kinematics with the vehicle’s dynamic model, we design a robust controller for the follower AUVs. ③We design a trajectory tracking controller using Back Stepping method for the leader AUV, import the formation feedback information into the trajectory tracking controller for the leader AUV, to solve the problem of formation feedback deficiency in leader-follower method, and obtain the auxiliary control law for the coordinated formation control of multi-AUV system. We use Lyapunov theory to prove the formation errors between leader and follower AUVs, and the speed tracking errors for the follower AUVs can converge to zero, the overall system is asymptotically stable. The Matlab simulation results verify the effectiveness of the robust controller for the follower AUVs and the coordinated formation controller for the leader AUV. 4. We perform innovative researching works for the moth-inspired collaborated CPT with multiple AUVs in following four aspects. ①We convert the formation control for the multi-AUV system into a reactive behavior of Keep-Formation for the follower AUVs, and design an adaptive behavior planner for the leader and follower AUVs, respectively. The leader and follower AUVs switch their social role and behaviors dynamically according to the PACS strategy and the adaptive behavior planner. ②Based on the analysis for the plume environment and the characteristics of collaborated CPT mission with multiple AUVs, we optimize the behavioral parameters for the Keep-Formation behavior and make estimation for the plume width. ③Based on the two formation configurations of strict and loose formation shape, we study coordinated path following for the cloverleaf trajectory, design a coordinated path following control system for the leader and follower AUVs, redesign the Reacquire-Plume behavior and optimize its behavioral parameters. ④We develop a simulation system for the collaborated CPE with multiple AUVs, which provides a demonstration platform for the collaborated CPE mission. A large number of Monte Carlo simulation results show the rationality and effectiveness of all four aspects’ works. 5. Aimed at the complex dynamic plume environments, weak communication conditions and the distribution characteristics of the plume in spatial and temporal scales, and based on the source identification algorithms for a single AUV, we propose two collaborated source identification algorithms of C_SIZ_T (Collaborated SIZ_T) and C_SIZ_F (Collaborated SIZ_F) algorithm for multi-AUV system. We perform 1000 CPT test runs for both algorithms in the simulation platform for the collaborated CPE with multiple AUVs. Simulation results show the effectiveness of these two source identification algorithms. We make comparisons between the performances of CPE via a single AUV and collaborated CPE with multiple AUVs. Then we can draw a conclusion that the collaborated CPE with multiple AUVs is superior to the CPE via a single AUV in both CPT time cost and source identification errors. In addition, we also take full advantage of small ROV vehicle to perform pool and sea trial experiment researches that combined virtual and actual situations. In which, the real vehicle sails in the pool or at sea according to the plume tracking strategy, the virtual plume and ocean current information are supplied by the simulation system of CPE via a single AUV. This thesis validates the effectiveness of CPE via a single AUV with the scale of 10×10 meters in the pool and 100×100 meters at the sea. In summary, this thesis performs a comprehensive and systematic research on the collaborated CPE with multiple AUVs, by the ways of theoretical exploration combined with simulations, covers the whole process of searching and tracking the plume, and ultimately locating the source location, provides a feasible solution and laid the theoretical foundation for the future application of CPE with multi-AUV system.
语种: 中文
产权排序: 1
内容类型: 学位论文
URI标识: http://ir.sia.cn/handle/173321/9273
Appears in Collections:水下机器人研究室_学位论文

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Recommended Citation:
康小东.基于多水下机器人编队的化学羽流探测研究.[博士 学位论文].中国科学院沈阳自动化研究所.2010
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