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A Coalitional Distributed Model Predictive Control Perspective for a Cyber-Physical Multi-Agent Application.

Anca Maxim¹, Constantin-Florin Caruntu¹

¹Department of Automatic Control and Applied Informatics, "Gheorghe Asachi" Technical University of Iasi, 700050 Iasi, Romania.

Sensors (Basel, Switzerland)

|July 2, 2021

Summary

A new Coalitional Distributed Model Predictive Control (C-DMPC) strategy enhances control for interconnected cyber-physical systems. It ensures system functionality by forming coalitions when local optimization fails.

Keywords:

closed-loop stability coalitional model predictive control distributed model-predictive control multi-agent systems

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Area of Science:

Control Systems Engineering
Cyber-Physical Systems
Distributed Control

Background:

Increasing interconnectedness of physical systems via communication networks.
Need for advanced control strategies for multi-agent cyber-physical systems.
Limitations of classical Distributed Model Predictive Control (DMPC) in certain scenarios.

Purpose of the Study:

To develop a Coalitional Distributed Model Predictive Control (C-DMPC) strategy.
To create a flexible control architecture by integrating DMPC and Coalitional MPC.
To address challenges in controlling interconnected multi-agent systems.

Main Methods:

Development of a novel C-DMPC algorithm.
Simulation of a test scenario with four dynamically coupled subsystems.
Implementation of an unidirectional communication topology.

Main Results:

The C-DMPC strategy successfully maintained system functionality when local optimization feasibility was lost.
Coalition formation between neighboring agents resolved optimization shortcomings.
Demonstrated efficiency and performance of the proposed C-DMPC method.

Conclusions:

The proposed C-DMPC is effective for controlling interconnected cyber-physical systems.
Coalition formation is a viable mechanism to overcome local optimization challenges.
The C-DMPC strategy offers a robust solution for complex multi-agent control problems.