arXiv (All)
open access
Model-Free Control for Residential Heating: Deployment and Simulation of Nonlinear Data-Enabled Predictive Control
Residential heating accounts for a large share of building energy use, and predictive control strategies can reduce it by anticipating rather than reacting to the room temperature alone. The usual manner of implementing predictive control, model predictive control (MPC), requires an accurate model o
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Data-driven predictive control for building thermal management : a hierarchical framework comparing indirect and direct approaches#231589
- Data-driven adaptive building thermal controller tuning with constraints: A primal-dual contextual Bayesian optimization approach#625006
- Generalizing HVAC Control With Domain Randomized Reinforcement Learning#973447
- Very Exciting: Zero-Shot Model Predictive Control of Buildings via Excitation-Based Generalized Transfer Learning Models#1123239
- Identifying Vulnerable Population under Heat Stress: A Data-Driven Urban Risk Assessment Using Remote Sensing, Citizen Science and Census Data#31467
Record · ID 1035900
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive