Fast ADMM for distributed model predictive control of cooperative waterborne AGVs

Huarong Zheng*, Rudy R. Negenborn, G. Lodewijks

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

43 Citations (Scopus)


This brief proposes a distributed predictive path following controller with arrival time awareness for multiple waterborne automated guided vessels (waterborne AGVs) applied to interterminal transport (ITT). The goal is to design an efficient cooperative distributed algorithm that solves local problems in parallel and minimizes an overall objective. We model the ITT problem using waterborne AGVs with independent dynamics and objectives but coupling collision avoidance constraints. The problem is then solved by distributed model predictive control (DMPC) of which the parallelism is realized using the alternating direction method of multipliers (ADMM). Successive linearizations are utilized to maintain a tradeoff among computational complexity, optimality, and ease of decomposition. Moreover, we propose a fast ADMM by iteratively incorporating in local problems adaptive global information to improve convergence rates. Simulation results for an ITT case study illustrate the effectiveness of the proposed algorithms for DMPC of time-varying networks in general and cooperative distributed waterborne AGVs in particular.

Original languageEnglish
Article number7572966
Pages (from-to)1406-1413
JournalIEEE Transactions on Control Systems Technology
Issue number4
Publication statusPublished - 2017


  • Collision avoidance
  • cooperative parallel control
  • distributed model predictive control (DMPC)
  • fast alternating direction method of multipliers (ADMM)
  • Waterborne automated guided vessels (waterborne AGVs).


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