A robust data|driven model predictive thermal control for rack|based ...

A robust data-driven model predictive thermal control for rack-based ...

In this paper, a robust data-driven model predictive control (MPC) method for air-cooled rack-based DCs, based on Willems fundamental lemma, is proposed.

A robust data-driven model predictive thermal control for rack-based ...

Download Citation | On Oct 1, 2024, Yiran Li and others published A robust data-driven model predictive thermal control for rack-based data ...

Data-Driven Robust Model Predictive Control on Building Climate ...

However, thermal comfort would violate the constraints if uncertainties in weather forecasts are not effectively accounted for. Robust MPC (RMPC) could protect ...

A Data-driven Subspace Predictive Control Method for Air-cooled ...

Request PDF | A Data-driven Subspace Predictive Control Method for Air-cooled Data Center Thermal Modelling and Optimization | This paper ...

Efficient Greenhouse Temperature Control with Data-Driven Robust ...

Efficient Greenhouse Temperature Control with Data-Driven Robust Model Predictive ... based control, certainty equivalent MPC, and robust MPC. DDRMPC ...

Data-driven Model Predictive Control Research Articles - R Discovery

A robust data-driven model predictive thermal control for rack-based data center. Optimizing and controlling of air-cooled data centers cooling systems are ...

Thermal Comfort Control on Sustainable Building via Data-Driven ...

We propose a data-driven robust model predictive control (DDRMPC) framework to address climate control of a sustainable building with renewable hybrid energy ...

Model Predictive Evolutionary Temperature Control via Neural ...

In this study, we propose a population-based, data-driven intelligent controller that leverages neural-network-based digital twins for hypothesis testing.

Robust MPC with data-driven demand forecasting for frequency ...

... models to demand forecasts here. By combining a control scheme based on Robust Model Predictive Control, with affine policies, and heating ...

Data-driven robust model predictive control for greenhouse ...

... control framework for greenhouse temperature control and its energy utilisation assessment in the presence of uncertainties. First, an analytical model based ...

Data-Driven Robust Optimization for Greenhouse Temperature ...

This work proposes a novel data-driven robust model predictive control (DDRMPC) framework for automatic control of greenhouse temperature and CO 2 ...

Data-Driven Robust Optimal Operation of Thermal Energy Storage ...

Standard model predictive control scheme with data flow between optimizer and the system. Using notation analogous to problem (17), the scenario-based ...

[PDF] Robust Model Predictive Control of Irrigation Systems With ...

... based approach by constructing uncertainty sets from historical data ... A data-driven robust model predictive control approach for greenhouse temperature control ...

NMPC 2024 Program | Thursday August 22, 2024 - IFAC Papercept

... data-driven predictive control (DeePC) approach based on time series data. ... Abstract: In this paper, a data-driven distributed model predictive control ...

Multi-zone building control with thermal comfort constraints under ...

This paper proposes a novel data-driven robust model predictive control (MPC) framework for a multi-zone building considering thermal comfort and uncertain ...

Smart greenhouse control under harsh climate conditions based on ...

You, Semiclosed greenhouse climate control under uncertainty via machine learning and data-driven robust model predictive control, IEEE Trans. Control Syst.

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 ...

Adaptive Data-Driven Prediction in a Building Control Hierarchy - arXiv

Although linear models can approximate building thermal dynamics well, they do not fully account for the slow time-varying nature of buildings, which are ...

Review on model predictive control: an engineering perspective

A neural network (NN) is a non-linear empirical model based on historic data. ... of ilc–mpc controller with data-driven approach for constrained batch ...

Nonlinear model predictive control of a conductance-based neuron ...

We used recent advances in data-driven forecasting to construct a nonlinear machine-learning model of a Hodgkin–Huxley type neuron when only the membrane ...