TAILIEUCHUNG - Optimization method in designing a finite time average consensus protocol

In this paper, the optimization methods in designing a finite-time average consensus protocol for multi-agent systems or wireless sensor network are taken into account. As we all know, the purpose of the average consensus protocol is that all agents reach the final common value, which is the average of the initial values. | ISSN 1859-1531 - THE UNIVERSITY OF DANANG, JOURNAL OF SCIENCE AND TECHNOLOGY, NO. 12(133).2018 1 OPTIMIZATION METHOD IN DESIGNING A FINITE-TIME AVERAGE CONSENSUS PROTOCOL Tran Thi Minh Dung The University of Danang - University of Science and Technology; ttmdung@ Abstract - In this paper, the optimization methods in designing a finite-time average consensus protocol for multi-agent systems or wireless sensor network are taken into account. As we all know, the purpose of the average consensus protocol is that all agents reach the final common value, which is the average of the initial values. In order to run a consensus protocol, there are 2 main steps: self-configuration step, and execution step. In the selfconfiguration step, the consensus protocol is designed and uploaded to each agent of the system so that the final average value is achieved in the minimal execution time. The proposed optimization method is based on learning and training methods applied for neural network. Key words - Consensus protocols; finite-time average consensus protocols; back-propagation method; self-configuration; matrix factorization; learning method. 1. Introduction Recent years have witnessed the increasing number of studies devoted to multi-agent systems and wireless sensors networks. Several issues are then formulated as a consensus problem, which is to design a network protocol based on the local information obtained by each agent so that all agents finally reach an agreement on certain quantities of interest. The network protocol is an interaction rule, which ensures that the whole group can achieve a consensus on the shared data in a distributed manner, . without the coordination of a central authority. Consensus problems of multi-agent systems [1] have received tremendous attention from various research communities due to their broad applications in many areas including multi-sensor data fusion, multi-vehicle formation control, distributed computation and many .

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• Back propagation method
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