Data|driven learning|based Model Predictive Control for energy ...

Data-driven learning-based Model Predictive Control for energy ...

This paper proposes a data-driven learning-based Model Predictive Control (MPC) method for the integrated control of various devices in energy-intensive ...

Data-driven learning-based Model Predictive Control for energy ...

To address such problems, this paper proposes a data-driven learning-based Model Predictive Control (MPC) method for the integrated control of various devices ...

Data-driven Model Predictive and Reinforcement Learning Based ...

Classical model predictive control (MPC) has shown its capacity to reduce building energy consumption, but it suffers from labor-intensive ...

Data-driven learning-based Model Predictive Control for energy ...

Request PDF | On Oct 1, 2023, Jiawei Chen and others published Data-driven learning-based Model Predictive Control for energy-intensive systems | Find, ...

Energy Management Using Deep Learning-Based Model Predictive ...

Learn how to control a house heating system using nonlinear model predictive control (MPC) with a data-driven prediction model.

Efficient Data-Driven MPC for Demand Response of Commercial ...

Model predictive control (MPC) has been shown to significantly improve the energy efficiency of buildings while maintaining thermal comfort.

(PDF) Data-driven Model Predictive and Reinforcement Learning ...

In this work, we first present a compact review of the recent advances in data-driven MPC and RL-based control methods for building energy management.

Learning-Based Model Predictive Control for Energy Management ...

... learning algorithm addresses real-time decisions based on real-time data. The problem is solved for various sets of houses. Results ...

Data-Driven Model Predictive Control for Wave Energy Converters ...

... control methods is relatively underdeveloped in the literature. This study fills this gap. Gaussian Process (GP) is a powerful kernel-based learning method ...

Interpretable Data-Driven Model Predictive Control of Building ...

Data-driven model predictive control for power demand ...

... learning model for energy use forecast ... A support vector regression based model predictive control for volt-var optimization of distribution ...

Data-driven learning-based Model Predictive Control for energy ...

Data-driven learning-based Model Predictive Control for energy-intensive systems. https://doi.org/10.1016/j.aei.2023.102208 ·. Journal: Advanced Engineering ...

Interpretable data-driven model predictive control of building energy ...

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:222-234, 2024. Abstract. Advanced building energy system controls, such as ...

Data-Driven Model Predictive Control for Hybrid Charging Stations ...

An increased demand in electric vehicle (EV) charging facilities has necessitated intelligent energy management systems (EMSs), to control and monitor the ...

Combining Data-driven and Physics-based Process Models for ...

Model predictive control is well suited to control building energy systems efficiently. However, it still lacks commercial relevance due to the high ...

4 Data-Driven Model Predictive Control with Regression Trees—An ...

In many applications, such as build- ing control for energy management, Demand Response, or peak power reduction, obtaining a high-fidelity physics-based model ...

Data-driven model predictive control using random forests for ...

To overcome this problem, we introduce a novel idea for predictive control based on historical building data leveraging machine learning algorithms like ...

Learning strategies for data-driven model predictive control of building

Model predictive control is a promising approach to increase energy efficiency in buildings and tackle climate change. Based on a mathematical model of the ...

Data-Driven Model Predictive Control with Regression Trees—An ...

Madhur Behl, Achin Jain, and Rahul Mangharam. 2016. Data-driven modeling, control and tools for cyber-physical energy systems. In Proceedings of ...

Data-driven model predictive control using random forests for ...

To overcome this problem, the authors introduce a novel idea for predictive control based on historical building data leveraging machine learning algorithms ...