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Event-triggered Consensus Frameworks for Multi-agent Systems


Event-triggered Consensus Frameworks for Multi-agent Systems

Amini, Amir ORCID: https://orcid.org/0000-0002-2134-4406 (2020) Event-triggered Consensus Frameworks for Multi-agent Systems. PhD thesis, Concordia University.

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Recently, distributed multi-agent systems (MAS) have been widely studied for a variety of engineering applications, including cooperative vehicular systems, sensor networks, and electrical power grids. To solve the allocated tasks in MASs, each agent autonomously determines the appropriate actions using information available locally and received from its neighbours. Many cooperative behaviours in MAS are based
on a consensus algorithm. Consensus, by definition, is to distributively agree on a parameter of interest between the agents. Depending on the application, consensus has different configurations such as leader-following, formation, synchronization in robotic arms, and state estimation in sensor networks. Consensus in MASs requires local measurements and information exchanges between the neighbouring agents. Due to the energy restriction, hardware limitation, and bandwidth constraint, strategies that reduce the amount of measurements and information exchanges between the
agents are of paramount interest. Event-triggering transmission schemes are among the most recent strategies that efficiently reduce the number of transmissions. This dissertation proposes a number of event-triggered consensus (ETC) implementations
which are applicable to MASs. Different performance objectives and physical constraints, such as a desired convergence rate, robustness to uncertainty in control realization, information quantization, sampled-data processing, and resilience to denial
of service (DoS) attacks are included in realization of the proposed algorithms. A novel convex optimization is proposed which simultaneously designs the control and event-triggering parameters in a unified framework. The optimization governs the trade-off between the consensus convergence rate and intensity of transmissions. This co-design optimization is extended to an advanced class of event-triggered schemes,
known as the dynamic event-triggering (DET), which is able to substantially reduce the amount of transmissions. In the presence of DoS attacks, the co-design optimization simultaneously computes the control and DET parameters so that the number of transmissions is reduced and a desired level of resilience to DoS is guaranteed. In addition to consensus, a formation-containment implementation is proposed, where the
amount of transmissions are reduced using the DET schemes. The performance of the proposed implementations are evaluated through simulation over several MASs. The
experimental results demonstrate the effectiveness of the proposed implementations and verify their design flexibility.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (PhD)
Authors:Amini, Amir
Institution:Concordia University
Degree Name:Ph. D.
Program:Electrical and Computer Engineering
Date:3 October 2020
Thesis Supervisor(s):Asif, Amir and Mohammadi, Arash
ID Code:987588
Deposited By: Amir Amini
Deposited On:29 Jun 2021 20:48
Last Modified:29 Jun 2021 20:48
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