Volume 13, Issue 3 (March 2026), Pages: 198-206

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 Original Research Paper

Consensus-based model predictive control for scalable multi-robot coordination

 Author(s): 

Faheed A. F. Alrslani *

 Affiliation(s):

Department of Information Technology, Faculty of Computing and Information Technology, Northern Border University, Rafha, Saudi Arabia

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 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0000-0001-5957-6467

 Digital Object Identifier (DOI)

  https://doi.org/10.21833/ijaas.2026.03.020

 Abstract

Creating scalable, secure, and real-time coordination in decentralized multi-agent systems remains a major challenge. Centralized planning approaches often suffer from limited scalability and weak robustness, while purely decentralized methods may lead to inefficient behavior or deadlocks. This paper proposes a hierarchical framework that integrates Decentralized Model Predictive Control (MPC) with an intention-sharing consensus protocol. The coordination problem is formulated as a constrained stochastic optimal control problem, and Sequential Convex Programming (SCP) is applied to efficiently solve the non-convex trajectory optimization problems encountered by individual agents at the local level. At the higher level, a consensus protocol enables agents to actively resolve conflicts and align their intentions, thereby reducing short-sighted decision-making. Extensive simulations on challenging benchmark scenarios show that the proposed approach achieves performance close to centralized methods and significantly outperforms existing reactive and predictive baselines in terms of success rate, efficiency, and safety. Furthermore, the method demonstrates strong robustness to communication delays, sensor noise, and model uncertainty, indicating its suitability for real-world applications.

 © 2026 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

Multi-agent systems, Decentralized model predictive control, Consensus protocols, Sequential convex programming, Trajectory optimization

 Article history

Received 18 October 2025, Received in revised form 10 March 2026, Accepted 14 March 2026

 Acknowledgment

The author gratefully acknowledges the Deanship of Scientific Research at Northern Border University, Arar, KSA, for funding this research work through the project number “NBU-FFR-2025-1662-01.” 

 Compliance with ethical standards

 Citation:

Alrslani FAF (2026). Consensus-based model predictive control for scalable multi-robot coordination. International Journal of Advanced and Applied Sciences, 13(3): 198-206

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