scholarly journals Developing Communication Strategy for Multi-Agent Systems with Incremental Fuzzy Model

2018 ◽  
Vol 9 (8) ◽  
Author(s):  
Sam Hamzeloo ◽  
Mansoor Zolghadri
Keyword(s):  
Fuzzy Model ◽  
Communication Strategy ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Output consensus for heterogeneous nonlinear multi-agent systems based on T-S fuzzy model

2016 ◽  
Vol 30 (5) ◽  
pp. 1042-1060 ◽  
Author(s):  
Xiaolei Li ◽  
Xiaoyuan Luo ◽  
Shaobao Li ◽  
Xinping Guan
Keyword(s):  
Fuzzy Model ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Consensus of high-order feed-forward non-linear systems with low gain and communication constraints

2018 ◽  
Vol 41 (4) ◽  
pp. 1101-1109
Author(s):  
Xuehui Mei ◽  
Zhiyong Yu ◽  
Haijun Jiang ◽  
Cheng Hu
Keyword(s):  
High Order ◽  
Communication Strategy ◽  
Time Varying ◽  
Multi Agent Systems ◽  
Feed Forward ◽  
Agent Systems ◽  
Time Varying Delay ◽  
Non Linear ◽  
Multi Agent ◽  
Varying Delay

In this paper, the consensus problem of high-order multi-agent systems with inherent feed-forward delayed non-linear dynamics is investigated. First, a new kind of aperiodically intermittent communication strategy, which can be regarded as an extension of continuous communication, is proposed. The time-varying delay is considered in the multi-agent systems and the delay is not restricted to less than the communication width. Moreover, in order to reach a consensus, the effect of the feed-forward non-linearity and the time-varying delay is eliminated by designing a low-gain control protocol. Based on Lyapunov stability theory, graph theory and inequality techniques, some sufficient conditions related to the input gain and the communication width are obtained for achieving the consensus. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed method.

scholarly journals A Fully Distributed Protocol with an Event-Triggered Communication Strategy for Second-Order Multi-Agent Systems Consensus with Nonlinear Dynamics

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4059
Author(s):  
Tao Li ◽  
Quan Qiu ◽  
Chunjiang Zhao
Keyword(s):  
Nonlinear Dynamics ◽  
Laplacian Matrix ◽  
Second Order ◽  
Communication Strategy ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Leader Following ◽  
Multi Agent ◽  
Matrix Spectrum ◽  
Event Triggered

This paper presents the communication strategy for second-order multi-agent systems with nonlinear dynamics. To address the problem of the scarcity of communication channel resources and get rid of using continuous signals among the followers in lead-follower multi-agent systems, a novel event-triggered communication mechanism is proposed in this paper. To avoid employing the centralized information that depends on the Laplacian matrix spectrum, a network protocol with updated coupling gains is proposed, as well as an event-triggered strategy with updated thresholds. To eliminate the ill effects of inter-node communicating noise, relative positions are employed by the protocol instead of absolute positions. By a Lyapunov–Krasovskii functional, it is rigorously proven that the leader-following consensus of MASs is achieved without Zeno behavior, under the control of the proposed protocol with an event-triggered mechanism communication. The effectiveness of the proposed protocol is verified through numerical examples.

scholarly journals Learning Agent Communication under Limited Bandwidth by Message Pruning

2020 ◽  
Vol 34 (04) ◽  
pp. 5142-5149
Author(s):  
Hangyu Mao ◽  
Zhengchao Zhang ◽  
Zhen Xiao ◽  
Zhibo Gong ◽  
Yan Ni
Keyword(s):  
Reinforcement Learning ◽  
Control Policy ◽  
Communication Strategy ◽  
Multi Agent Systems ◽  
Agent Communication ◽  
Limited Bandwidth ◽  
Agent Systems ◽  
Gating Mechanism ◽  
Learning Agent ◽  
Multi Agent

Communication is a crucial factor for the big multi-agent world to stay organized and productive. Recently, Deep Reinforcement Learning (DRL) has been applied to learn the communication strategy and the control policy for multiple agents. However, the practical limited bandwidth in multi-agent communication has been largely ignored by the existing DRL methods. Specifically, many methods keep sending messages incessantly, which consumes too much bandwidth. As a result, they are inapplicable to multi-agent systems with limited bandwidth. To handle this problem, we propose a gating mechanism to adaptively prune less beneficial messages. We evaluate the gating mechanism on several tasks. Experiments demonstrate that it can prune a lot of messages with little impact on performance. In fact, the performance may be greatly improved by pruning redundant messages. Moreover, the proposed gating mechanism is applicable to several previous methods, equipping them the ability to address bandwidth restricted settings.

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