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Safe Control of Multi-Agent Systems with Minimal Communication

Mo Yang, Jing Yu, Necmiye Ozay

TL;DR

This work formulates the problem of safety-assured, minimal-communication control for multi-agent systems as a rank-minimization task over distributed gains, incorporating fixed inter-agent delays. By leveraging System Level Synthesis (SLS), the authors provide a convex relaxation that expresses safety and delay constraints in terms of closed-loop response maps Φ, and derive an upper bound linking the inter-agent communication rank to Φ, enabling a nuclear-norm surrogate. The proposed encoder/decoder structure realizes a low-communication controller with provable sparsity patterns, and numerical experiments across two- and four-vehicle scenarios show substantial reductions in inter-agent transmissions compared to baselines, while maintaining safety. A stated limitation is the theoretical focus on two-agent networks, with future work to generalize the results and analyze delay effects more deeply.

Abstract

In many multi-agent systems, communication is limited by bandwidth, latency, and energy constraints. Designing controllers that achieve coordination and safety with minimal communication is critical for scalable and reliable deployment. This paper presents a method for designing controllers that minimize inter-agent communication in multi-agent systems while satisfying safety and coordination requirements, while conforming to communication delay constraints. The control synthesis problem is cast as a rank minimization problem, where a convex relaxation is obtained via system level synthesis. Simulation results on various tasks, including trajectory tracking with relative and heterogeneous sensing, demonstrate that the proposed method significantly reduces inter-agent transmission compared to baseline approaches.

Safe Control of Multi-Agent Systems with Minimal Communication

TL;DR

This work formulates the problem of safety-assured, minimal-communication control for multi-agent systems as a rank-minimization task over distributed gains, incorporating fixed inter-agent delays. By leveraging System Level Synthesis (SLS), the authors provide a convex relaxation that expresses safety and delay constraints in terms of closed-loop response maps Φ, and derive an upper bound linking the inter-agent communication rank to Φ, enabling a nuclear-norm surrogate. The proposed encoder/decoder structure realizes a low-communication controller with provable sparsity patterns, and numerical experiments across two- and four-vehicle scenarios show substantial reductions in inter-agent transmissions compared to baselines, while maintaining safety. A stated limitation is the theoretical focus on two-agent networks, with future work to generalize the results and analyze delay effects more deeply.

Abstract

In many multi-agent systems, communication is limited by bandwidth, latency, and energy constraints. Designing controllers that achieve coordination and safety with minimal communication is critical for scalable and reliable deployment. This paper presents a method for designing controllers that minimize inter-agent communication in multi-agent systems while satisfying safety and coordination requirements, while conforming to communication delay constraints. The control synthesis problem is cast as a rank minimization problem, where a convex relaxation is obtained via system level synthesis. Simulation results on various tasks, including trajectory tracking with relative and heterogeneous sensing, demonstrate that the proposed method significantly reduces inter-agent transmission compared to baseline approaches.

Paper Structure

This paper contains 11 sections, 4 theorems, 11 equations, 5 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Problem Statement
  3. Convex relaxation via SLS
  4. System level synthesis (SLS)
  5. Reformulation via SLS
  6. Numerical Evaluation
  7. Distance tracking under asymmetric control and noise
  8. Trajectory tracking with various sensing scenarios
  9. Four vehicles chasing with relative measurement
  10. Conclusion
  11. Proof of \ref{['lem:phi-rank']}

Key Result

Lemma 1

For all $i,\, j \in \mathcal{N}$, there exists a causal factorization of matrix $\mathbf{K}^{ij}$ such that $\mathbf{K}^{ij} =\mathbf{D}^{ij}\mathbf{E}^{ij}$ with $r^{ij} = \text{rank}\left(\mathbf{K}^{ij}\right)$. Moreover, there exists $\{t_k\}_{k\in[r^{ij}]}$ such that $0 \leq t_1 \leq t_2 \leq \

Figures (5)

  • Figure 1: Local controller structure with encoder and decoder where $\mathbf{D}^{ij}$ and $\mathbf{E}^{ij}$ are defined in \ref{['eq:DE']}.
  • Figure 2: Two sets of trajectories generated by proposed controller for the experiment with asymmetric control and noise.
  • Figure 3: Four sets of trajectories generated by proposed controller in experiments of two vehicles with different sensing strategies.
  • Figure 4: Relationship between delay and the number of message for the baseline and proposed controller in experiment with heterogeneous sensing vehicles.
  • Figure 5: Four sets of trajectories generated by proposed controller designed for four vehicles with relative measurements. Different colors of start and end boxes correspond to the vehicle trajectories with the same color.

Theorems & Definitions (5)

  • Lemma 1: aspeel2023low
  • Proposition 1
  • Lemma 2: hassaan2022system
  • Proposition 2
  • Remark 1