Handling Plant Variation via Error-Triggered On-line Model Identification: Application to Economic Model Predictive Control**Financial support from the National Science Foundation and the Department of Energy is gratefully acknowledged.

Model Identification ◽

Department Of Energy ◽

Plant Variation ◽

National Science ◽

On Line

Fault-Tolerant Economic Model Predictive Control Using Empirical Models * *Financial support from the National Science Foundation and the Department of Energy is gratefully acknowledged

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2017.08.940 ◽

2017 ◽

Vol 50 (1) ◽

pp. 3517-3523

Author(s):

Anas Alanqar ◽

Helen Durand ◽

Panagiotis D. Christofides

Keyword(s):

Predictive Control ◽

Economic Model ◽

Financial Support ◽

Fault Tolerant ◽

Empirical Models ◽

Department Of Energy ◽

National Science

Error-triggered on-line model identification in economic model predictive control

2016 American Control Conference (ACC) ◽

10.1109/acc.2016.7525175 ◽

2016 ◽

Author(s):

Anas Alanqar ◽

Helen Durand ◽

Panagiotis D. Christofides

Keyword(s):

Predictive Control ◽

Economic Model ◽

Model Identification ◽

Line Model ◽

On Line

Empirical Modeling of Control Valve Layer with Application to Model Predictive Control-Based Stiction Compensation**Financial support from the National Science Foundation and the Department of Energy is gratefully acknowledged.

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2016.10.137 ◽

2016 ◽

Vol 49 (18) ◽

pp. 41-46

Author(s):

Helen Durand ◽

Panagiotis D. Christofides

Keyword(s):

Predictive Control ◽

Financial Support ◽

Control Valve ◽

Department Of Energy ◽

Empirical Modeling ◽

National Science

Fast Economic Model Predictive Control for a Gas Lifted Well Network ⁎ ⁎The authors gratefully acknowledge the financial support from Research Council of Norway through IKTPLUSS Young Researcher Grant and SFI SUBPRO programs.

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2018.06.350 ◽

2018 ◽

Vol 51 (8) ◽

pp. 25-30 ◽

Cited By ~ 2

Author(s):

Eka Suwartadi ◽

Dinesh Krishnamoorthy ◽

Johannes Jäschke

Keyword(s):

Predictive Control ◽

Economic Model ◽

Financial Support ◽

Research Council ◽

Young Researcher ◽

Economic Model Predictive Control

Fault-Tolerant Economic Model Predictive Control Using Error-Triggered Online Model Identification

Industrial & Engineering Chemistry Research ◽

10.1021/acs.iecr.7b00576 ◽

2017 ◽

Vol 56 (19) ◽

pp. 5652-5667 ◽

Cited By ~ 10

Author(s):

Anas Alanqar ◽

Helen Durand ◽

Panagiotis D. Christofides

Keyword(s):

Predictive Control ◽

Economic Model ◽

Fault Tolerant ◽

Model Identification ◽

Economic Model Predictive Control

Data-Based Nonlinear Model Identification in Economic Model Predictive Control

Smart and Sustainable Manufacturing Systems ◽

10.1520/ssms20180025 ◽

2018 ◽

Vol 2 (2) ◽

pp. 20180025 ◽

Cited By ~ 3

Author(s):

Laura Giuliani ◽

Helen Durand

Keyword(s):

Predictive Control ◽

Nonlinear Model ◽

Economic Model ◽

Model Identification ◽

Nonlinear Model Identification

Average Constraints in Robust Economic Model Predictive Control∗∗The authors would like to thank the German Research Foundation (DFG) for financial support of the project within the Cluster of Excellence in Simulation Technology (EXC 310/2) at the University of Stuttgart.

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2015.08.155 ◽

2015 ◽

Vol 48 (8) ◽

pp. 44-49

Author(s):

Florian A. Bayer ◽

Matthias A. MUller ◽

Frank Allgower

Keyword(s):

Predictive Control ◽

Economic Model ◽

Financial Support ◽

Simulation Technology ◽

German Research Foundation ◽

German Research ◽

The University

Distributed Economic MPC with Safety-Based Constraints for Nonlinear Systems * *Financial support from the National Science Foundation and the Department of Energy is gratefully acknowledged.

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2017.08.2098 ◽

2017 ◽

Vol 50 (1) ◽

pp. 12033-12040 ◽

Cited By ~ 1

Author(s):

Fahad Albalawi ◽

Helen Durand ◽

Panagiotis D. Christofides

Keyword(s):

Nonlinear Systems ◽

Financial Support ◽

Department Of Energy ◽

National Science

Handling Parametric Drift in Batch Crystallization Using Predictive Control with R2R Model Parameter Estimation∗∗Financial support from the Extreme Science and Engineering Discovery Environment (TG-CCR120003), the National Science Foundation (CBET-0967291), and the NSF Graduate Research Fellowship (DGE-1144087) given to Michael Nayhouse is gratefully acknowledged.

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2015.09.086 ◽

2015 ◽

Vol 48 (8) ◽

pp. 912-917 ◽

Cited By ~ 1

Author(s):

Joseph Sangil Kwon ◽

Michael Nayhouse ◽

Dong Ni Panagiotis D. Christofides

Keyword(s):

Parameter Estimation ◽

Predictive Control ◽

Financial Support ◽

Science And Engineering ◽

Batch Crystallization ◽

Research Fellowship ◽

Graduate Research ◽

National Science ◽

Parametric Drift

Review for "Hierarchical smart energy management strategy based on cooperative distributed economic model predictive control for multi‐microgrids systems"

10.1002/2050-7038.12732/v4/review2 ◽

2020 ◽

Keyword(s):

Energy Management ◽

Predictive Control ◽

Economic Model ◽

Management Strategy ◽

Energy Management Strategy ◽

Smart Energy Management