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第三十九届中国控制会议

作者： Yuanhui Wang Weijie Xie Xiaoyun Zhang College of Automation Harbin Engineering University Harbin Marine Boiler and Turbine Research Institute

It focuses on solving the problem of autonomous obstacle avoidance for unmanned surface vehicles（USVs） formation ***,a three-degree-of-freedom kinematics and dynamic model of USV is ***,the flocking algorithm is used to solve the problem of autonomous formation control for *** the flocking algorithm is generally applied to particle-based model,it can’t be directly applied to underactuated ***,a virtual force point is introduced and a force analysis is carried out,which converts the control inputs in the flocking algorithm into the longitudinal control and heading *** this case,it can achieve the autonomous formation of the USVs and the purpose of tracking virtual ***,combining obstacle avoidance algorithm based on potential function with flocking algorithm to achieve obstacle avoidance for the formation ***,the effectiveness of the algorithm and model is verified by simulation experiments.

关键词： USV Formation Control Obstacle Avoidance flocking algorithm Virtual Leader

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flocking Control of Multiple AUVs Based on Fuzzy Potential Functions

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2018年第5期26卷 2539-2551页

作者： Sahu, Basant Kumar Subudhi, Bidyadhar Natl Inst Sci & Technol Dept Elect Engn Berhampur 761008 Orissa India Natl Inst Technol Dept Elect Engn Rourkela 769008 India

This paper presents the formulation of a flocking control algorithm for a group of autonomous underwater vehicles (AUVs). A leader-follower control strategy is employed to flock a group of AUVs along a predefined desired path. In this approach, leader AUVs are assumed to have global knowledge of the desired trajectory and the follower AUVs are not provided with this information. For keeping all the AUVs connected in a group, a flocking center is estimated. This flocking center is a virtual point whose position at any instant of time can he predicted by using a consensus algorithm. The controllers for the leader and follower AUVs are developed by implementing mathematical and fuzzy artificial potential functions. A group of four AUVs is considered for analyzing the efficacy of the developed control algorithm. Simulations are carried out both in obstacle-free and obstacle-rich environments. From the obtained results, it is observed that the proposed fuzzy flocking control algorithm provides effective cooperative motion control of multiple AUVs along the desired paths and avoid obstacles successively. It is also observed that the flocking controller developed based on fuzzy artificial potential function outperforms the controller with mathematical potential functions despite uncertainties owing to external disturbances.

关键词： Artificial potential function consensus algorithm flocking algorithm fuzzy potential function

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Self-triggered distributed model predictive control for flocking of multi-agent systems

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IET CONTROL THEORY AND APPLICATIONS 2018年第18期12卷 2441-2448页

作者： Hu, Yanjie Zhan, Jingyuan Li, Xiang Fudan Univ Dept Elect Engn Adapt Networks & Control Lab Shanghai 200433 Peoples R China Fudan Univ Sch Informat Sci & Engn Res Ctr Smart Networks & Syst Shanghai 200433 Peoples R China Beijing Univ Technol Coll Metropolitan Transportat Beijing Key Lab Transportat Engn Beijing 100124 Peoples R China

This study presents a self-triggered distributed model predictive control algorithm for the flock of a multi-agent system. All the agents in a flock are endowed with the capability of determining the sampling time adaptively to reduce the unnecessary energy consumption in communication and control updates. The agents are dynamically decoupled in a flock, and each agent is driven by a local model predictive controller, which is designed by minimising the position irregularity between the agent and its neighbours, velocity tracking errors as well as its control efforts. Moreover, the collision avoidance is considered by introducing constraints in the model predictive minimisation problem. In order to adaptively determine the sampling time, a self-triggered algorithm is designed by guaranteeing the decrease of the Lyapunov function. Finally, numerical simulations are given to demonstrate the feasibility of the proposed flocking algorithm.

关键词： predictive control distributed control multi-robot systems collision avoidance Lyapunov methods minimisation numerical analysis mobile robots multiagent system unnecessary energy consumption local model predictive controller model predictive minimisation problem flocking algorithm control update self-triggered distributed model predictive control algorithm sampling time determination communication update position irregularity minimisation velocity tracking errors collision avoidance Lyapunov function numerical simulations

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Application of Robot Operating System in Robot Flocks 10

Application of Robot Operating System in Robot Flocks

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IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)

作者： Fernandes, Jordan Li, Keye Mirabile, Joey Vesonder, Gregg Stevens Inst Technol Sch Syst & Enterprises Hoboken NJ 07030 USA

ISBN: (纸本)9781728138855

flocking behavior is an exercise in both control and coordination. Members need to move in near-perfect time with each other to maintain a safe, but compact, distance amongst themselves. This balance could have a number of useful applications, ranging from automated vehicles to power grid coordination. Moreover, per Reynolds (1987), flocking behavior can be summarized as an algorithm, which automated systems can easily consume. Inspired by this premise, the group blueprinted a robot flock using Turtlebot3 Burgers and Robot Operating System, or ROS. To begin, the group created an algorithm in Scratch, a graphical programming language. Per Reynolds' model, as long as each individual member knows and follows the algorithm, a flock will form without any outside influence. The group theorized that this modular approach would bide well with the ROS system of nodes and messages. By deeming each member a flocking node and having a remote "master" perform functions such as localization, the ROS framework would naturally support robot flocking. However, after transcribing their program to C++, the group found some ongoing issues in development. They struggled to adapt ROS's message commands into their program, and the Burgers' given localization program had trouble supporting a multi-robot flock. Regardless, with further research, the group still believes that ROS can give rise to a viable flock.

关键词： ROS Turtlebot3 flocking algorithm flocking simulation Transform mapping Autonomous systems

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Distributed Formation Control of Autonomous Underwater Vehicles Based on flocking and Consensus algorithms 10th

Distributed Formation Control of Autonomous Underwater Vehic...

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10th International Conference on Intelligent Robotics and Applications (ICIRA

作者： Pan, Wuwei Jiang, Dapeng Pang, Yongjie Qi, Yuda Luo, Daichao Harbin Engn Univ Sci & Technol Underwater Vehicle Lab Harbin 150001 Peoples R China

ISBN: (纸本)9783319652894;9783319652887

In this paper, a distributed formation controller of autonomous underwater vehicles is presented. An artificial potential field is proposed based on the Lennard-Jones potential. A weight function is designed to make the potential smoothly die off at the boundaries. A control algorithm is proposed according to the three rules of Reynolds: flock centering, collision avoidance and velocity matching. A single-step target tracking method is proposed to translate the desired acceleration, produced by the potential force, to the desired velocity and heading for the AUV. To make the algorithm distributed, each AUV holds a copy of the virtual leader and calculates the guidance information individually. A consensus algorithm is proposed to make the mismatches convert to zeros. A fold line and a curve line path following of the fleet are simulated, with random initial positions of the AUVs. Under the formation control algorithms proposed, the AUVs are uniformly distributed and form a lattice-like formation. We increase the number of AUVs, and the algorithm serves well, which shows good availability and flexibility.

关键词： Autonomous underwater vehicle Distributed control Formation control flocking algorithm Consensus algorithm

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Distributed estimation and control of mobile sensor networks based only on position measurements

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IET CONTROL THEORY AND APPLICATIONS 2017年第10期11卷 1627-1633页

作者： Jin, Dingshou Zeng, Wei Su, Housheng Zhou, Hongtao Delie, Ming Huazhong Univ Sci & Technol Guangdong Prov Key Lab Digital Mfg Equipment Image Proc & Intelligent Control Key LabEduc Min Guangdong HUST Ind Technol Res InstSch Automat Wuhan 430074 Peoples R China

Most existing distributed estimation and control algorithms for mobile sensor networks rely on the information of both position and velocity of neighbour sensors. The authors' investigate the distributed estimation and control of mobile sensor network with only position measurements. Based on the Kalman-consensus filter and the flocking algorithm, all mobile sensors move to a target, and achieve consensus on the estimations of the target. Under the assumption that the initial interactive network is connected, the stability of the cascading system is proved via Lyapunov stability theory and matrix principle. Moreover, a sufficient stability condition in the form of the boundary conditions of the feedback gain is proposed for the mobile sensor network. Some numerical examples are provided to illustrate the effectiveness of theoretical results.

关键词： wireless sensor networks Kalman filters position control distributed control Lyapunov methods stability matrix algebra distributed estimation mobile sensor networks position measurements neighbour sensors Kalman-consensus filter flocking algorithm Lyapunov stability theory matrix principle stability condition wireless sensor network

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Distributed Cooperative flocking Control for Multiple Mobile Robots Based on IoT 9th

Distributed Cooperative Flocking Control for Multiple Mobile...

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9th International Conference on Internet and Distributed Computing Systems (IDCS)

作者： Wang, Qiang Li, Aosong Zhu, Tian Wuhan Univ Technol Sch Logist Engn Wuhan 430063 Hubei Peoples R China

ISBN: (纸本)9783319459394;9783319459400

Control of multiple mobile robots raises fundamental and novel problems in controlling the structure of the resulting dynamic graphs, particularly in applications involving the Internet of Things. This paper studies the distributed cooperative control problem of agent groups in the context of multi-agent flocking tasks with second order linear dynamics. A distributed flocking algorithm is proposed which is composed of two parts: motion strategy based on virtual units and stable flocking algorithm with bounded control input. The proposed algorithm handles the movement and reconfiguration of the flock under the environment of Internet of Things (IoT), while maintaining the desired shape for the initial dis-connected network. Experimental results demonstrate the effectiveness of the algorithm as a means to guarantee flocking in a team of robots.

关键词： Mobile robots IoT flocking algorithm

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Design of Interval Type-2 Fuzzy Logic Controllers for flocking algorithm

Design of Interval Type-2 Fuzzy Logic Controllers for Flocki...

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IEEE International Conference on Fuzzy Systems (FUZZ 2011)

作者： Lee, Seung-Mok Kim, Jong-Hwan Myung, Hyun Korea Adv Inst Sci & Technol Dept Civil & Environm Engn Robot Program Taejon 305701 South Korea Korea Adv Inst Sci & Technol Dept Elect & Comp Engn Robot Program Taejon 305701 South Korea

ISBN: (纸本)9781424473175

This paper presents a novel interval type-2 fuzzy logic control architecture for flocking system when the system has noisy sensor measurements. The traditional type-1 fuzzy logic controller (FLC) using precise type-1 fuzzy sets cannot fully model and handle the uncertainties of sensor data. However, type-2 FLC using type-2 fuzzy sets with a footprint of uncertainty (FOU) produces better performances under noisy environments. In this paper, therefore, we present a reactive control architecture for flocking algorithm that is based on interval type-2 FLC to implement the flocking behaviors consisting separation, obstacle avoidance, and velocity matching behaviors. The type-2 based control system could cope with the uncertainties of noisy sensor measurements and resulted in good performances that outperformed the type-1 FLC.

关键词： Type-2 fuzzy logic controller (FLC) flocking algorithm reactive control multi-agent systems

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Cluster-based Position Tracking of Mobile Sensors

Cluster-based Position Tracking of Mobile Sensors

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IEEE Conference on Wireless Sensors (ICWiSE)

作者： Kumar, Vikram Bergmann, Neil W. Ahmad, Izanoordina Jurdak, Raja Kusy, Branislav Univ Queensland Sch Informat Tech & Elec Engn Brisbane Qld Australia CSIRO Data61 Pullenvale Australia

ISBN: (纸本)9781509016266

Tracking movement of mobile nodes has received significant scientific and commercial interest, but long term tracking of resource-constrained mobile nodes remains challenging due to the high energy consumption of satellite receivers. Cooperative position tracking has been proposed for energy efficiency, however, all the cooperative schemes use opportunistic cooperation and optimize for either energy or accuracy. Considering the existence of a reasonably stable group of mobile nodes like animals, birds, and mobile assets, we propose a cluster-based cooperative tracking algorithm, where cluster head centrally coordinates resource usage among cluster members. Variants of this strategy include the use of a cooperative Kalman filter with and without inertial sensor inputs to estimate nodes' positions. We use the Boid flocking algorithm to generate group position movements in 3D and perform various experiments to compare the energy and position accuracy tradeoff of our proposed scheme with individual-based tracking and existing cooperative schemes. We perform the experiments for fixed periodic GPS sampling and dynamic GPS sampling triggered by node position error uncertainty tolerance limit. Experiments results show that in periodic sampling scheme cooperative tracking yields more than one-quarter reduction in energy consumption and more than one-third improvement in position accuracy over individual-based tracking, however, results for dynamic sampling scheme are comparable with existing cooperative scheme.

关键词： group tracking cooperative localization energy-accuracy tradeoff cooperative Kalman filter energy efficient tracking flocking algorithm cluster based tracking

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flocking algorithm with multi-target tracking for multi-agent systems

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PATTERN RECOGNITION LETTERS 2010年第9期31卷 800-805页

作者： Luo, Xiaoyuan Li, Shaobao Guan, Xinping Yanshan Univ Dept Elect Engn Qinhuangdao 066004 Peoples R China

This paper investigates a flocking algorithm with multi-target tracking for multi-agent systems. It is supposed that every target can accept a certain number of agents. Which target is chosen by an agent is determined by the distances from the agent to the targets and the number of agents accepted by targets. Based on whether agents move toward the same target or toward separate targets, two kinds of potential functions are presented to carry out the flocking algorithm. Then the inputs of the dynamic system can be obtained. Under the driving of the inputs, agents with the same target can make a flocking during the tracking process, and the agents with different targets separate from each other. A time-varying parameter is designed to control the maximum velocity of agents in the proposed algorithm. Lyapunov stability theorem is applied to prove the stability of the dynamic system. Finally, simulation results verify the effectiveness of the proposed algorithm. (c) 2010 Elsevier B.V. All rights reserved.

关键词： Multi-agent Multi-target Potential function flocking algorithm

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