Data-Enabled Predictive Control for Optimal Pressure Management
Recent developments in control theory coupled with the growing availability of real-time data have paved the way for improved data-driven control methodologies. This study explores the application of a data-enabled predictive control (DeePC) algorithm to optimize the operation of water distribution...
Saved in:
| Main Authors: | Gal Perelman, Avi Ostfeld |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-08-01
|
| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/69/1/5 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Data Enabled Predictive Control for Water Distribution Systems Optimization
by: Gal Perelman, et al.
Published: (2025-04-01) -
Optimizing Time Series Models for Water Demand Forecasting
by: Gal Perelman, et al.
Published: (2024-08-01) -
A novel data-driven NLMPC strategy for techno-economic microgrid management with battery energy storage under uncertainty
by: Elnaz Yaghoubi, et al.
Published: (2025-08-01) -
Optimized Predictive Coverage by Averaging Time‐Windowed Bayesian Distributions
by: Han‐Fang Hsueh, et al.
Published: (2024-05-01) -
Transient Pressure Estimation Using Data-Driven Models: An Approach Based on Ensemble Trees
by: Rafael Barreto, et al.
Published: (2024-09-01)