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Vol. 1,  No. 1, 2014

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SPECIAL ISSUE PAPERS
An Overview of Distributed High-order Multi-agent Coordination
Jie Huang, Hao Fang, Lihua Dou, Jie Chen
2014, 1(1): 1-9.
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Research on multi-agent systems has attracted much attention in the past two decades, and numerous results have been obtained. Its widespread applications include spacecraft, mobile robots, sensor networks, etc. Most previous research works on multi-agent systems studied the first- and second-order ...
On Dynamics and Nash Equilibriums of Networked Games
Daizhan Cheng, Tingting Xu, Fenghua He, Hongsheng Qi
2014, 1(1): 10-18.
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Networked noncooperative games are investigated, where each player (or agent) plays with all other players in its neighborhood. Assume the evolution is based on the fact that each player uses its neighbors' current information to decide its next strategy. By using sub-neighborhood, the dynamics of t...
Leader-following Rendezvous with Connectivity Preservation of Single-integrator Multi-agent Systems
Yi Dong, Jie Huang
2014, 1(1): 19-23.
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This paper studies the problem of leader-following rendezvous with connectivity preservation for a linear multiagent system where the leader system is a linear autonomous system and the follower system is a multiple single-integrator system. We develop a distributed state feedback control protocol t...
Optimal Deployment of Mobile Sensors for Target Tracking in 2D and 3D Spaces
Shiyu Zhao, Ben M Chen, Tong H Lee
2014, 1(1): 24-30.
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This paper proposes a control strategy to autonomously deploy optimal placements of range-only mobile sensors in 2D and 3D spaces. Based on artificial potential approaches, the control strategy is designed to minimize the intersensor and external potentials. The inter-sensor potential is the objecti...
Road Pricing Design Based on Game Theory and Multi-agent Consensus
Nan Xiao, Xuehe Wang, Lihua Xie, Tichakorn Wongpiromsarn, Emilio Frazzoli, Daniela Rus
2014, 1(1): 31-39.
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Consensus theory and noncooperative game theory respectively deal with cooperative and noncooperative interactions among multiple players/agents. They provide a natural framework for road pricing design, since each motorist may myopically optimize his or her own utility as a function of road price a...
Distributed Self-triggered Control for Consensus of Multi-agent Systems
Hao Zhang, Gang Feng, Huaicheng Yan, Qijun Chen
2014, 1(1): 40-45.
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This paper studies the consensus problem of general linear multi-agent systems via self-triggered control. Two distributed self-triggered control schemes based on state feedback and output feedback are developed respectively. It is shown that under the proposed control protocols, consensus can be re...
Distributed Control of Nonlinear Uncertain Systems: A Cyclic-small-gain Approach
Tengfei Liu, Zhongping Jiang
2014, 1(1): 46-53.
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This paper presents a cyclic-small-gain approach to distributed control of nonlinear multi-agent systems for output agreement. Through a novel nonlinear control law design, the output agreement problem is transformed into a stabilization problem, and the closed-loop multi-agent system is transformed...
Experimental Verification of a Multi-robot Distributed Control Algorithm with Containment and Group Dispersion Behaviors: the Case of Dynamic Leaders
Hejin Zhang, Zhiyun Zhao, Ziyang Meng, Zongli Lin
2014, 1(1): 54-60.
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This paper studies the containment and group dispersion control for a multi-robot system in the presence of dynamic leaders. Each robot is represented by a doubleintegrator dynamic model and a distributed control algorithm is developed to drive the multi-robot system to follow a group of dynamic lea...
An Approximate Gradient Algorithm for Constrained Distributed Convex Optimization
Yanqiong Zhang, Youcheng Lou, Yiguang Hong
2014, 1(1): 61-67.
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In this paper, we propose an approximate gradient algorithm for the multi-agent convex optimization problem with constraints. The agents cooperatively compute the minimum of the sum of the local objective functions which are subject to a global inequality constraint and a global constraint set. Inst...
Cooperative Localization of AUVs Using Moving Horizon Estimation
Sen Wang, Ling Chen, Dongbing Gu, Huosheng Hu
2014, 1(1): 68-76.
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This paper studies the localization problem of autonomous underwater vehicles (AUVs) constrained by limited size, power and payload. Such AUVs cannot be equipped with heavy sensors which makes their underwater localization problem difficult. The proposed cooperative localization algorithm is perform...
Adaptive Neural Region Tracking Control of Multi-fully Actuated Ocean Surface Vessels
Xiaoming Sun, Shuzhi Sam Ge
2014, 1(1): 77-83.
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In this paper, adaptive neural network region tracking control is designed to force a group of fully actuated ocean vessels with limited sensing range to track a common moving target region, in the presence of uncertainties and unknown disturbances. In this control concept, the desired objective is ...
Tracking Control of Leader-follower Multi-agent Systems Subject to Actuator Saturation
Airong Wei, Xiaoming Hu, Yuzhen Wang
2014, 1(1): 84-91.
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This paper addresses the tracking problem of leaderfollower multi-agent systems subject to actuator saturation. A leader node or command generator is considered, which generates the desired tracking trajectory. To track such a leader, a new family of scheduled low-and-high-gain feedback controllers ...
Decentralised Formation Control and Stability Analysis for Multi-vehicle Cooperative Manoeuvre
Aolei Yang, Wasif Naeem, Minrui Fei
2014, 1(1): 92-100.
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Multi-vehicle cooperative formation control problem is an important and typical topic of research on multi-agent system. This paper presents a formation stability conjecture to conceive a new methodology for solving the decentralised multivehicle formation control problem. It employs the "extensiond...
Decentralized Adaptive Filtering for Multi-agent Systems with Uncertain Couplings
Hongbin Ma, Yini Lv, Chenguang Yang, Mengyin Fu
2014, 1(1): 101-112.
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In this paper, the problem of decentralized adaptive filtering for multi-agent systems with uncertain couplings is formulated and investigated. This problem is challenging due to the mutual dependency of state estimation and coupling estimation. First, the problem is divided into four typical types ...