Cover Image

Economic zone data-enabled predictive control for connected open water systems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Xiaoqiao, Zhang, Xuewen, Han, Minghao, Law, Adrian Wing-Keung, Yin, Xunyuan
Format:	Preprint
Published:	2025
Subjects:	Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Efficient Economic Model Predictive Control of Water Treatment Process with Learning-based Koopman Operator
by: Han, Minghao, et al.
Published: (2024)

Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling
by: Yan, Mingxue, et al.
Published: (2024)

Reduced-order Koopman modeling and predictive control of nonlinear processes
by: Zhang, Xuewen, et al.
Published: (2024)

Economic data-enabled predictive control using machine learning
by: Yan, Mingxue, et al.
Published: (2025)

MAKO: Meta-Adaptive Koopman Operators for Learning-based Model Predictive Control of Parametrically Uncertain Nonlinear Systems
by: Han, Minghao, et al.
Published: (2025)

Partition-based distributed extended Kalman filter for large-scale nonlinear processes with application to chemical and wastewater treatment processes
by: Li, Xiaojie, et al.
Published: (2024)

Learning-based data-enabled economic predictive control with convex optimization for nonlinear systems
by: Yan, Mingxue, et al.
Published: (2025)

Deep DeePC: Data-enabled predictive control with low or no online optimization using deep learning
by: Zhang, Xuewen, et al.
Published: (2024)

Deep Neural Koopman Operator-based Economic Model Predictive Control of Shipboard Carbon Capture System
by: Han, Minghao, et al.
Published: (2025)

Machine learning-based hybrid dynamic modeling and economic predictive control of carbon capture process for ship decarbonization
by: Zhang, Xuewen, et al.
Published: (2025)

Lyapunov-based reinforcement learning for distributed control with stability guarantee
by: Yao, Jingshi, et al.
Published: (2024)

Machine learning-based input-augmented Koopman modeling and predictive control of nonlinear processes
by: Li, Zhaoyang, et al.
Published: (2024)

Learning-based data-enabled moving horizon estimation with application to membrane-based biological wastewater treatment process
by: Li, Xiaojie, et al.
Published: (2026)

Self‐tuning moving horizon estimation of nonlinear systems via physics‐informed machine learning Koopman modeling
by: Mingxue Yan, et al.
Published: (2024)

Smart energy management: process structure-based hybrid neural networks for optimal scheduling and economic predictive control in integrated systems
by: Wu, Long, et al.
Published: (2024)

Data-driven parallel Koopman subsystem modeling and distributed moving horizon state estimation for large-scale nonlinear processes
by: Li, Xiaojie, et al.
Published: (2024)

Distributed Observer and Controller Design for Linear Systems: A Separation-Based Approach
by: Cao, Ganghui, et al.
Published: (2025)

Distributed Omniscient Observers for Multi-Agent Systems: Design and Applications
by: Cao, Ganghui, et al.
Published: (2026)

Approximating arrival costs in distributed moving horizon estimation: A recursive method
by: Li, Xiaojie, et al.
Published: (2024)

Iterative distributed moving horizon estimation of linear systems with penalties on both system disturbances and noise
by: Li, Xiaojie, et al.
Published: (2024)

Communication-Efficient Decentralized Multi-Agent Reinforcement Learning for Cooperative Adaptive Cruise Control
by: Chen, Dong, et al.
Published: (2023)

Online Reduced-Order Data-Enabled Predictive Control
by: Vahidi-Moghaddam, Amin, et al.
Published: (2024)

Extending direct data-driven predictive control towards systems with finite control sets
by: Klädtke, Manuel, et al.
Published: (2024)

An overview of systems-theoretic guarantees in data-driven model predictive control
by: Berberich, Julian, et al.
Published: (2024)

An AI-enabled dual-hormone model predictive control algorithm that delivers insulin and pramlintide
by: Jacobs, Peter G., et al.
Published: (2025)

Performance triggered adaptive model reduction for soil moisture estimation in precision irrigation
by: Debnath, Sarupa, et al.
Published: (2024)

Kernelized offset-free data-driven predictive control for nonlinear systems
by: de Jong, Thomas Oliver, et al.
Published: (2024)

Energy-efficient predictive control for connected, automated driving under localization uncertainty
by: Joa, Eunhyek, et al.
Published: (2024)

Reservoir computing for system identification and predictive control with limited data
by: Williams, Jan P., et al.
Published: (2024)

On data usage and predictive behavior of data-driven predictive control with 1-norm regularization
by: Klädtke, Manuel, et al.
Published: (2025)

Clustering-enhanced adaptive Benders decomposition for energy systems planning optimization
by: Law, Jun Wen, et al.
Published: (2026)

Towards explainable data-driven predictive control with regularizations
by: Klädtke, Manuel, et al.
Published: (2025)

Implicit predictors in regularized data-driven predictive control
by: Klädtke, Manuel, et al.
Published: (2023)

Sample- and computationally efficient data-driven predictive control
by: Alsalti, Mohammad, et al.
Published: (2023)

Approximate predictive control barrier function for discrete-time systems
by: Didier, Alexandre, et al.
Published: (2024)

Data-driven $H_{\infty}$ predictive control for constrained systems: a Lagrange duality approach
by: Wu, Wenhuang, et al.
Published: (2024)

On the impact of regularization in data-driven predictive control
by: Breschi, Valentina, et al.
Published: (2023)

Robust and efficient data-driven predictive control
by: Alsalti, Mohammad, et al.
Published: (2024)

Average predictive control for nonlinear discrete dynamical systems
by: Dmitrishin, D., et al.
Published: (2019)

Dynamic modeling and predictive control of a microfluidic system
by: Martinez, Jorge Vicente, et al.
Published: (2024)