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Found 7 papers, 2 papers with code
Data/moment-driven approaches for fast predictive control of collective dynamics
The high-dimensional character of collective dynamics hampers the performance of traditional MPC algorithms based on fast online dynamic optimization at every time step.
Multi-level Optimal Control with Neural Surrogate Models
Optimal actuator and control design is studied as a multi-level optimisation problem, where the actuator design is evaluated based on the performance of the associated optimal closed loop.
Data-driven initialization of deep learning solvers for Hamilton-Jacobi-Bellman PDEs
A deep learning approach for the approximation of the Hamilton-Jacobi-Bellman partial differential equation (HJB PDE) associated to the Nonlinear Quadratic Regulator (NLQR) problem.
Gradient-augmented Supervised Learning of Optimal Feedback Laws Using State-dependent Riccati Equations
A supervised learning approach for the solution of large-scale nonlinear stabilization problems is presented.
Collisionless and Decentralized Formation Control for Strings
A decentralized feedback controller for multi-agent systems, inspired by vehicle platooning, is proposed.
Optimization and Control Multiagent Systems Dynamical Systems Adaptation and Self-Organizing Systems
Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic in England
A mathematical model for the COVID-19 pandemic spread in England is presented.
Applications Physics and Society Populations and Evolution
Tensor Decomposition Methods for High-dimensional Hamilton-Jacobi-Bellman Equations
For nonlinear dynamics, the effectiveness of the high-dimensional control synthesis method is assessed in the optimal feedback stabilization of the Allen-Cahn and Fokker-Planck equations with a hundred of variables.
Optimization and Control Numerical Analysis Numerical Analysis
