Heterogeneous unknown multi-agent systems over switching networks: a distributed optimal coordination design
Reza Naseri, Amir Abolfazl Suratgar, Mohammad Bagher Menhaj · International Journal of Systems Science · 2025
This study explores the distributed optimal coordination problem for Linear Time-Invariant Multi-Agent Systems (MAS). Each agent has its cost function. The goal is to control the agents to minimise the combined cost function, which sums their individual costs. Unlike previous studies that rely on known agent dynamics for control design, our research assumes the dynamics are almost entirely unknown. Additionally, the communication topology is assumed to change over time in a switching manner. We propose a novel distributed control framework with two layers to tackle this challenge. The top layer searches for the minimiser and provides a reference signal to the bottom layer. The bottom layer uses adaptive controllers to enable agents to track the reference signal and approach the minimiser. It is not enough for the reference trajectories to converge to the minimiser; they must also be feasible for the agents to follow. The unknown dynamics and switching communication graph make this task more complex. Our framework addresses these challenges by applying Model Reference Adaptive Control (MRAC) principles. We validate the theoretical results through numerical simulations and provide practical examples to show the approach’s applicability in real-world scenarios.