Open Access

ARTICLE

Consensus Control Design for Heterogeneous Multi–Agent Systems in Vehicle Platooning Using an Event–Triggering Scheme

Muhammad Shamrooz Aslam^1,#, Wen-Jer Chang^2,*, Hazrat Bilal^3,*, Vyacheslav Gulvanskii⁴, Dmitrii Perevertaylo⁴, Dmitrii Kaplun^1,4,5, Muhammad Hashim Bukhari⁶, Muhammad Aamir Aman^7,#,*

1 School of Computer Science and Technology/School of Artificial Intelligence, China University of Mining and Technology, Xuzhou, China
2 Department of Marine Engineering, National Taiwan Ocean University (NTOU), Keelung, Taiwan
3 Center for AI Research (CAIR), University of Agder (UiA), Grimstad, Norway
4 Intelligent Devices Institute, Saint Petersburg Electrotechnical University “LETI”, Saint Petersburg, Russia
5 Higher School of Artificial Intelligence Technologies, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia
6 Saudi Aramco LIP Star Building, Dhahran, Saudi Arabia
7 School of Electrical Engineering, China University of Mining and Technology, Xuzhou, China

* Corresponding Authors: Wen-Jer Chang. Email: ; Hazrat Bilal. Email: ; Muhammad Aamir Aman. Email:
# These authors contributed equally to this work

Computer Modeling in Engineering & Sciences 2026, 148(3), 1 https://doi.org/10.32604/cmes.2026.084958

Received 02 May 2026; Accepted 12 August 2026; Issue published 28 September 2026

Abstract

In a multi-agent system, platoon vehicles receive a huge collection regarding autonomous models coordinating and their actions to improve traffic flow, lower fuel consumption, and boost safety. This paper examines the distributed consensus control problem for heterogeneous multi–agent systems (MASs) containing both first-order and second-order agents, under constrained network communication resources. Secondly, a novel event–triggered approach is proposed to tackle the problems of information transmission restrictions and bandwidth contention. Unlike conventional state-independent triggering methods, the proposed trigger condition depends on both the agent’s own state update error and the information mismatches between neighboring agents, enabling a balanced trade–off between control performance and communication reduction. By ensuring that the transmission interval always exceeds one sampling period, the event-triggered technique significantly reduces network bandwidth usage. It determines the next transmission time for both position and velocity information. Thirdly, sufficient criteria for reaching asymptotic consensus are determined using Lyapunov stability theory and Kronecker product features. The trigger parameters and controller gains are obtained by solving linear matrix inequalities (LMIs). The distributed event–triggering mechanism and the consensus control protocol are integrated into a co-design framework. The effectiveness of the suggested strategy in conserving network resources without sacrificing system stability is validated by simulation results for a heterogeneous MAS with two second–order and two first–order agents, which show that all agent states converge to common values while the number of information transmissions is significantly reduced compared to periodic sampling.

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Keywords

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