# Distributed Nonlinear MPC of Multi-Agent Systems with Data Compression and Random Delays - Extended Version

arXiv: https://arxiv.org/abs/1504.03494 · HTML: https://mlsanity.com/paper/1504.03494/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Apr 2015.

## Built on by (most cited first, 2 of 2)

- [Toward Scalable Multirobot Control: Fast Policy Learning in Distributed MPC](https://mlsanity.com/paper/2412.19669/) (2024)
- [Communication Reduction via Semantic-Based Encoding in DMPC Using LSTMs](https://mlsanity.com/paper/2608.17592/) (2026)

## Abstract (arXiv)

This is an extended version of a technical note accepted for publication in IEEE Transactions on Automatic Control. The note proposes an Input to State practically Stable (ISpS) formulation of distributed nonlinear model predictive controller (NMPC) for formation control of constrained autonomous vehicles in presence of communication bandwidth limitation and transmission delays. Planned trajectories are compressed using neural networks resulting in considerable reduction of data packet size, while being robust to propagation delays and uncertainty in neighbors' trajectories. Collision avoidance is achieved by means of spatially filtered potential field. Analytical results proving ISpS and generalized small gain conditions are presented for both strongly- and weakly-connected networks, and illustrated by simulations.