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6412. Distributed aggregative optimization with quantized communication
- Creator:
- Chen, Ziqin and Liang, Shu
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- multi-agent network, linear convergence rate, distributed aggregative optimization, and quantized communication
- Language:
- English
- Description:
- In this paper, we focus on an aggregative optimization problem under the communication bottleneck. The aggregative optimization is to minimize the sum of local cost functions. Each cost function depends on not only local state variables but also the sum of functions of global state variables. The goal is to solve the aggregative optimization problem through distributed computation and local efficient communication over a network of agents without a central coordinator. Using the variable tracking method to seek the global state variables and the quantization scheme to reduce the communication cost spent in the optimization process, we develop a novel distributed quantized algorithm, called D-QAGT, to track the optimal variables with finite bits communication. Although quantization may lose transmitting information, our algorithm can still achieve the exact optimal solution with linear convergence rate. Simulation experiments on an optimal placement problem is carried out to verify the correctness of the theoretical results.
- Rights:
- http://creativecommons.org/licenses/by-nc-sa/4.0/ and policy:public
6413. Distributed approach to neuroinformatics data interchange
- Creator:
- Řeřucha , Šimon
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- Neuroinformatics, data exchange, distributed database, and data standardization
- Language:
- English
- Description:
- One of the problems during a great disaster is the breakdown of communication infra structure. One of the solutions is the use of mobile ad-hoc networks (MANET). In this paper, we consider the situation in a building after a big fire, explosion or earthquake. Rescue workers equipped with PDAs, which are wireless connected, explore the dynamically changing world. Each individual builds up a local world map based on their local exploration and observation. The local maps are fused via the MANET structure and provide an up to date map of the dynamically changing world. Such maps can be used for mitigation, escape or rescue work.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
6414. Distributed consensus control for discrete-time linear multi-agent systems with reduced-order observer
- Creator:
- Chen, Wenhai, Gao, Lixin, Xu, Xiaole, and Xu, Bingbing
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- multi-agent system, discrete-time system, distributed control, consensus, and observer
- Language:
- English
- Description:
- In this paper, we investigate multi-agent consensus problem with discrete-time linear dynamics under directed interaction topology. By assumption that all agents can only access the measured outputs of its neighbor agents and itself, a kind of distributed reduced-order observer-based protocols are proposed to solve the consensus problem. A multi-step algorithm is provided to construct the gain matrices involved in the protocols. By using of graph theory, modified discrete-time algebraic Riccati equation and Lyapunov method, the proposed protocols can be proved to solve the discrete-time consensus problem. Furthermore, the proposed protocol is generalized to solve the model-reference consensus problem. Finally, a simulation example is given to illustrate the effectiveness of our obtained results.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
6415. Distributed deployment algorithm based on boundary expansion and virtual force for mobile sensor networks
- Creator:
- Nan, Guofang , Chen, Zhongnan, Li, Minqiang, Huang, Liang , and Abraham, Ajith
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- Wireless sensor networks, sensor deployment, network connectivity, virtual force, and boundary expansion
- Language:
- English
- Description:
- Optimization of sensors position is a challenging problem in wireless sensor networks since the processing process significantly affects energy consumption, surveillance ability and network lifetime. Vectorbased algorithm (VEC) and Voronoi-based algorithm (VOR) are two existing approaches. However, VEC is sensitive to initial deployment, while VOR always moves to the coverage holes. Moreover, the nodes in a network may oscillate for a long time before they reach the equilibrium state. This paper presents an initially central deployment model that is cost effective and easy to implement. In this model, we present a new distributed deployment algorithm based on boundary expansion and virtual force (BEVF). The proposed scheme enables nodes to move to the boundary rapidly and ultimately reach equilibrium quickly. For a node, only the location of its nearby nodes and boundary information are needed in the algorithm, thereby avoiding communication cost for transmitting global information. The distance threshold is adopted to limit node movement and to avoid node oscillations. Finally, we compare BEVF with existing algorithms Results show that the proposed algorithm achieves a much larger coverage and consumes lower energy.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
6416. Distributed event-triggered algorithm for optimal resource allocation of multi-agent systems
- Creator:
- Yu, Weiyong, Deng, Zhenhua, Zhou, Hongbing, and Zeng, Xianlin
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- distributed optimization, event-triggered strategy, multi-agent systems, and resource allocation
- Language:
- English
- Description:
- This paper is concerned with solving the distributed resource allocation optimization problem by multi-agent systems over undirected graphs. The optimization objective function is a sum of local cost functions associated to individual agents, and the optimization variable satisfies a global network resource constraint. The local cost function and the network resource are the private data for each agent, which are not shared with others. A novel gradient-based continuous-time algorithm is proposed to solve the distributed optimization problem. We take an event-triggered communication strategy and an event-triggered gradient measurement strategy into account in the algorithm. With strongly convex cost functions and locally Lipschitz gradients, we show that the agents can find the optimal solution by the proposed algorithm with exponential convergence rate, based on the construction of a suitable Lyapunov function. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed scheme.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
6417. Distributed event-triggered tracking control of leader-follower multi-agent systems with communication delays
- Creator:
- Hu, Jiangping, Chen, Guanrong, and Li, Han-Xiong
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- leader-follower multi-agent system, event-triggered control, time-varying delay, and directed topology
- Language:
- English
- Description:
- As embedded microprocessors are applied widerly to multi-agent systems, control scheduling and time-delay problems arose in the case of limited energy and computational ability. It has been shown that the event-triggered actuation strategy is an effective methodology for designing distributed control of multi-agent systems with limited computational resources. In this paper, a tracking control problem of leader-follower multi-agent systems with/without communication delays is formulated and a distributed dynamic tracking control is designed by employing event-triggered technique. Then, the input-to-state stability of the closed-loop multi-agent system with directed interconnections is analyzed. Finally, a numerical example is given to validate the proposed control.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
6418. Distributed filtering of networked dynamic systems with non-Gaussian noises over sensor networks: a survey
- Creator:
- Ding, Derui , Han, Qing-Long, and Ge, Xiaohua
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- sensor networks, non-Gaussian noises, network-induced phenomena, communication protocols, and distributed filtering
- Language:
- English
- Description:
- Sensor networks are regarded as a promising technology in the field of information perception and processing owing to the ease of deployment, cost-effectiveness, flexibility, as well as reliability. The information exchange among sensors inevitably suffers from various network-induced phenomena caused by the limited resource utilization and complex application scenarios, and thus is required to be governed by suitable resource-saving communication mechanisms. It is also noteworthy that noises in system dynamics and sensor measurements are ubiquitous and in general unknown but can be bounded, rather than follow specific Gaussian distributions as assumed in Kalman-type filtering. Particular attention of this paper is paid to a survey of recent advances in distributed filtering of networked dynamic systems with non-Gaussian noises over sensor networks. First, two types of widely employed structures of distributed filters are reviewed, the corresponding analysis is systematically addressed, and some interesting results are provided. The inherent purpose of adding consensus terms into the distributed filters is profoundly disclosed. Then, some representative models characterizing various network-induced phenomena are reviewed and their corresponding analytical strategies are exhibited in detail. Furthermore, recent results on distributed filtering with non-Gaussian noises are sorted out in accordance with different network-induced phenomena and system models. Another emphasis is laid on recent developments of distributed filtering with various communication scheduling, which are summarized based on the inherent characteristics of their dynamic behavior associated with mathematical models. Finally, the state-of-the-art of distributed filtering and challenging issues, ranging from scalability, security to applications, are raised to guide possible future research.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
6419. Distributed H∞ estimation for moving target under switching multi-agent network
- Creator:
- Chen, Hu, Weiwei, Qin, Bing, He, and Gang, Liu
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- multi-agent systems, distirbuted estimation, H∞ filter, and switching topology
- Language:
- English
- Description:
- In this paper, the distributed H∞ estimation problem is investigated for a moving target with local communication and switching topology. Based on the solution of the algebraic Riccati equation, a recursive algorithm is proposed using constant gain. The stability of the proposed algorithm is analysed by using the Lyapounov method, and a lower bound for estimation errors is obtained for the proposed common H∞ filter. Moreover, a bound for the H∞ parameter is obtained by means of the solution of the algebraic Riccati equation. Finally, a simulation example is employed to illustrate the effectiveness of the proposed estimation algorithm.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
6420. Distributed optimization for multi-agent system over unbalanced graphs with linear convergence rate
- Creator:
- Cheng, Songsong and Liang, Shu
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- multi-agent systems, distributed optimization, unbalanced graph, small gain theory, and linear convergence rate
- Language:
- English
- Description:
- Distributed optimization over unbalanced graphs is an important problem in multi-agent systems. Most of literatures, by introducing some auxiliary variables, utilize the Push-Sum scheme to handle the widespread unbalance graph with row or column stochastic matrix only. But the introduced auxiliary dynamics bring more calculation and communication tasks. In this paper, based on the in-degree and out-degree information of each agent, we propose an innovative distributed optimization algorithm to reduce the calculation and communication complexity of the conventional Push-Sum scheme. Furthermore, with the aid of small gain theory, we prove the linear convergence rate of the proposed algorithm.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public