Optimal consensus control of the Cucker-Smale model
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Abstract (arXiv)
We study the numerical realisation of optimal consensus control laws for agent-based models. For a nonlinear multi-agent system of Cucker-Smale type, consensus control is cast as a dynamic optimisation problem for which we derive first-order necessary optimality conditions. In the case of a smooth penalization fo the control energy, the optimality system is numerically approximated via a gradient-descent method. For sparsity promoting, non-smooth ℓ1-norm control penalizations, the optimal controllers are realised by means of heuristic methods. For an increasing number of agents, we discuss the approximation of the consensus control problem by following a mean-field modelling approach.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Feb 2018.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 2; 2025: 1; 2026: 1.
5 papers.
- 2021Mean Field Games Flock! The Reinforcement Learning Waycited by 31
- 2025Generative Models in Decision Making: A Surveycited by 15
- 2024Data/moment-driven approaches for fast predictive control of collective dynamicscited by 0
- 2024On the Effect of Instability on Learning Continuous-Time Linear Control Systemscited by 0
- 2026Schr"odinger Bridges over Kinetic Swarming Modelscited by 0
- 2026Schr"odinger Bridges over Kinetic Swarming Models26 Aug 2026
- 2025Generative Models in Decision Making: A Survey24 Feb 2025
- 2024On the Effect of Instability on Learning Continuous-Time Linear Control Systems17 Sep 2024
- 2024Data/moment-driven approaches for fast predictive control of collective dynamics23 Feb 2024
- 2021Mean Field Games Flock! The Reinforcement Learning Way17 May 2021