Model predictive control with random batch methods for a guiding problem
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Publication:5164243
DOI10.1142/S0218202521500329zbMath1476.49038arXiv2004.14834MaRDI QIDQ5164243
Publication date: 10 November 2021
Published in: Mathematical Models and Methods in Applied Sciences (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2004.14834
model predictive controlagent-based modelsrandom batch methodlarge scale complex systemsguiding problem
Numerical methods involving duality (49M29) Approximation methods and heuristics in mathematical programming (90C59) Design techniques (robust design, computer-aided design, etc.) (93B51)
Related Items (8)
Random Batch Methods for Classical and Quantum Interacting Particle Systems and Statistical Samplings ⋮ A framework for randomized time-splitting in linear-quadratic optimal control ⋮ Random-batch method for multi-species stochastic interacting particle systems ⋮ On the Random Batch Method for Second Order Interacting Particle Systems ⋮ Optimal control of nonlocal continuity equations: numerical solution ⋮ Convergence toward equilibrium of the first-order consensus model with random batch interactions ⋮ Uniform-in-time error estimate of the random batch method for the Cucker–Smale model ⋮ On the mean field limit of the random batch method for interacting particle systems
Uses Software
Cites Work
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- Sparse control of alignment models in high dimension
- Sparse stabilization and optimal control of the Cucker-Smale model
- A new model for self-organized dynamics and its flocking behavior
- Rapid solution of integral equations of classical potential theory
- Model predictive control: Theory and practice - a survey
- Mean-field Pontryagin maximum principle
- CasADi: a software framework for nonlinear optimization and optimal control
- Space mapping-based receding horizon control for stochastic interacting particle systems: dogs herding sheep
- Optimal strategies for driving a mobile agent in a ``guidance by repulsion model
- Random batch methods (RBM) for interacting particle systems
- Nonlinear model predictive control. Theory and algorithms
- A simple proof of the Cucker-Smale flocking dynamics and mean-field limit
- Sharp conditions to avoid collisions in singular Cucker-Smale interactions
- Criteria for global pinning-controllability of complex networks
- Synchronization and Transient Stability in Power Networks and Nonuniform Kuramoto Oscillators
- Convergence of a first-order consensus-based global optimization algorithm
- An analytical framework for consensus-based global optimization method
- Dynamics and control for multi-agent networked systems: A finite-difference approach
- Avoiding Collisions in Flocks
- Cucker-Smale Flocking With Inter-Particle Bonding Forces
- A consensus-based global optimization method for high dimensional machine learning problems
- Asymptotic behavior and control of a “guidance by repulsion” model
- Sparse Control of Hegselmann--Krause Models: Black Hole and Declustering
- Information Flow and Cooperative Control of Vehicle Formations
- Emergent Behavior in Flocks
- Flocking in Fixed and Switching Networks
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