Regularization in Data-driven Predictive Control: A Convex Relaxation Perspective
math.OC, cs.SY, eess.SY
Submitted: 2025-09-10
Updated: 2026-10-16
Code: https://github.com/soc-ucsd/Convex-Approximation-for-DeePC
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Policy Optimization in Control: Geometry and Algorithmic Implications
- Robust and efficient data-driven predictive control
- Data-based system representations from irregularly measured data
- Distributed Data-Driven Predictive Control for Multi-Agent Collaborative Legged Locomotion
- Harnessing Uncertainty for a Separation Principle in Direct Data-Driven Predictive Control
- On the Existence of Koopman Linear Embeddings for Controlled Nonlinear Systems
Related papers
- Lions and Muons: Optimization via Stochastic Frank-Wolfe under Heavy-Tailed Noise
- Adam-HNAG: A Convergent Reformulation of Adam with Accelerated Rate
- Incremental Learning in Mirror Flows
- Beyond Aggregate Drift: Optimal Client-Specific Windows in Federated Learning
- Lower Bounds for Randomized Linear-Oracle Optimization over Strongly Convex Sets
- Second-Order Optimization with Asynchronous Curvature