Frequency domain consensus control analysis of the networked multi-agent system with controller area network bus–induced delay

2021 ◽  
pp. 107754632110224
Author(s):  
Muhammad Nasir ◽  
Muhammad Faisal Hayat ◽  
Ayesha Jamal ◽  
Zahoor Ahmed
Keyword(s):  
Frequency Domain ◽  
Control Systems ◽  
Networked Control Systems ◽  
Controller Area Network ◽  
Networked Control ◽  
Area Network ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Consensus Control ◽  
Multi Agent

This article describes the consensus control issue of networked multi-agent system with controller area network bus–induced delay in the frequency domain. Initially, causes of the controller area network bus–induced delay in distributed networked control systems and features of controller area network buses are analyzed. Then, networked multi-agent systems composed of distributed networked control systems are modeled in the frequency domain. An analytical controller based on the parameterization technique is proposed to improve the H2 performance criterion of distributed networked control systems. The performance tracking and robustness of the controller is analyzed by its sensitivity functions. After the performance and robustness analysis, the delay margin criteria and consensus conditions of networked multi-agent systems are derived in the existence of controller area network bus–induced delay. We verify the efficiency of the proposed method by simulating examples.

scholarly journals Drone Swarms as Networked Control Systems by Integration of Networking and Computing

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2642
Author(s):  
Godwin Asaamoning ◽  
Paulo Mendes ◽  
Denis Rosário ◽  
Eduardo Cerqueira
Keyword(s):  
Control Systems ◽  
Networked Control Systems ◽  
Cooperative Behavior ◽  
Networked Control ◽  
Multi Agent Systems ◽  
Wireless Communication Network ◽  
Self Organized ◽  
Design Choice ◽  
Multi Agent ◽  
Computational Systems

The study of multi-agent systems such as drone swarms has been intensified due to their cooperative behavior. Nonetheless, automating the control of a swarm is challenging as each drone operates under fluctuating wireless, networking and environment constraints. To tackle these challenges, we consider drone swarms as Networked Control Systems (NCS), where the control of the overall system is done enclosed within a wireless communication network. This is based on a tight interconnection between the networking and computational systems, aiming to efficiently support the basic control functionality, namely data collection and exchanging, decision-making, and the distribution of actuation commands. Based on a literature analysis, we do not find revision papers about design of drone swarms as NCS. In this review, we introduce an overview of how to develop self-organized drone swarms as NCS via the integration of a networking system and a computational system. In this sense, we describe the properties of the proposed components of a drone swarm as an NCS in terms of networking and computational systems. We also analyze their integration to increase the performance of a drone swarm. Finally, we identify a potential design choice, and a set of open research challenges for the integration of network and computing in a drone swarm as an NCS.

scholarly journals Hybrid-order Network Consensus for Distributed Multi-agent Systems

2021 ◽  
Vol 70 ◽  
pp. 389-407
Author(s):  
Guangqiang Xie ◽  
Junyu Chen ◽  
Yang Li
Keyword(s):  
Higher Order ◽  
Distributed Artificial Intelligence ◽  
Order Structure ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Consensus Protocol ◽  
Consensus Control ◽  
Agent System ◽  
Agent Systems ◽  
Multi Agent

As an important field of Distributed artificial intelligence (DAI), multi-agent systems (MASs) have attracted the attention of extensive research scholars. Consensus as the most important issue in MAS, much progress has been made in studying the consensus control of MAS, but there are some problems remained largely unaddressed which cause the MAS to lose some useful network structure information. First, multi-agent consensus protocol usually proceeds over the low-order structure by only considering the direct edges between agents, but ignores the higher-order structure of the whole topology network. Second, the existing work assumes all the edges in a topology network have the same weight without exploring the potential diversity of the connections. In this way, multi-agent systems fail to enforce consensus, resulting in fragmentation into multiple clusters. To address the above issues, this paper proposes a Motif-aware Weighted Multi-agent System (MWMS) method for consensus control. We focus more on triangle motif in the network, but it can be extended to other kinds of motifs as well. First, a novel weighted network is used which is the combination of the edge-based lower-order structure and the motif-based higher-order structure, i.e., hybrid-order structure. Subsequently, by simultaneously considering the quantity and the quality of the connections in the network, a novel consensus framework for MAS is designed to update agents. Then, two baseline consensus algorithms are used in MWMS. In our experiments, we use ten topologies of different shapes, densities and ranges to comprehensively analyze the performance of our proposed algorithms. The simulation results show that the hybrid higher-order network can effectively enhance the consensus of the multi-agent system in different network topologies.

scholarly journals Multi-Agent Systems in Control Engineering: A Survey

2009 ◽  
Vol 2009 ◽  
pp. 1-12 ◽  
Author(s):  
Fatemeh Daneshfar ◽  
Hassan Bevrani
Keyword(s):  
Control Systems ◽  
Control Design ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Control Engineering ◽  
Agent Based ◽  
Agent Systems ◽  
Design And Implementation ◽  
Engineering Environment ◽  
Multi Agent

This paper presents a survey on multi-agent system (MAS) capabilities in control engineering applications. It describes essential concepts of multi-agent systems that are related to the control systems and presents an overview on the most important control engineering issues which MAS can be explored. Most important technical aspects in MAS implementation and development in engineering environment are also explained. Design methodologies, standards, tools, and supporting technologies to provide an effective MAS-based control design are addressed and a discussion on important related standards and protocols is given. Finally, some comments and new perspectives for design and implementation of agent-based control systems are presented.

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