Dinesh Krishnamoorthy
Dinesh Krishnamoorthy
Eindhoven University of Technology
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Cited by
Cited by
Steady-state real-time optimization using transient measurements
D Krishnamoorthy, B Foss, S Skogestad
Computers & Chemical Engineering 115, 34-45, 2018
Real-time optimization under uncertainty applied to a gas lifted well network
D Krishnamoorthy, B Foss, S Skogestad
Processes 4 (4), 52, 2016
Modelling and model predictive control of oil wells with electric submersible pumps
A Pavlov, D Krishnamoorthy, K Fjalestad, E Aske, M Fredriksen
2014 IEEE Conference on Control Applications (CCA), 586-592, 2014
Modelling and robustness analysis of model predictive control for electrical submersible pump lifted heavy oil wells
D Krishnamoorthy, EM Bergheim, A Pavlov, M Fredriksen, K Fjalestad
IFAC-PapersOnLine 49 (7), 544-549, 2016
Model predictive control with adaptive strategy applied to an electric submersible pump in a subsea environment
PA Delou, JPA de Azevedo, D Krishnamoorthy, MB de Souza Jr, ...
IFAC-PapersOnLine 52 (1), 784-789, 2019
Optimal operation of oil and gas production using simple feedback control structures
D Krishnamoorthy, K Fjalestad, S Skogestad
Control Engineering Practice 91, 104107, 2019
Robust extremum seeking control with application to gas lifted oil wells
D Krishnamoorthy, A Pavlov, Q Li
IFAC-PapersOnLine 49 (13), 205-210, 2016
Feedback real-time optimization strategy using a novel steady-state gradient estimate and transient measurements
D Krishnamoorthy, E Jahanshahi, S Skogestad
Industrial & Engineering Chemistry Research 58 (1), 207-216, 2018
On combining self-optimizing control and extremum-seeking control–applied to an ammonia reactor case study
J Straus, D Krishnamoorthy, S Skogestad
Journal of Process control 78, 78-87, 2019
A distributed feedback-based online process optimization framework for optimal resource sharing
D Krishnamoorthy
Journal of Process Control 97, 72-83, 2021
A distributed algorithm for scenario-based model predictive control using primal decomposition
D Krishnamoorthy, B Foss, S Skogestad
IFAC-PapersOnLine 51 (18), 351-356, 2018
Online process optimization with active constraint set changes using simple control structures
D Krishnamoorthy, S Skogestad
Industrial & Engineering Chemistry Research 58 (30), 13555-13567, 2019
Improving scenario decomposition for multistage MPC using a sensitivity-based path-following algorithm
D Krishnamoorthy, E Suwartadi, B Foss, S Skogestad, J Jäschke
IEEE control systems letters 2 (4), 581-586, 2018
Real-time optimization as a feedback control problem-a review
D Krishnamoorthy, S Skogestad
Computers & Chemical Engineering, 107723, 2022
Data-driven online adaptation of the scenario-tree in multistage model predictive control
M Thombre, D Krishnamoorthy, J Jäschke
IFAC-PapersOnLine 52 (1), 461-467, 2019
Data-driven scenario selection for multistage robust model predictive control
D Krishnamoorthy, M Thombre, S Skogestad, J Jäschke
IFAC-PapersOnLine 51 (20), 462-468, 2018
Gas lift optimization under uncertainty
D Krishnamoorthy, B Foss, S Skogestad
Computer Aided Chemical Engineering 40, 1753-1758, 2017
Plantwide control of an oil production network
E Jahanshahi, D Krishnamoorthy, A Codas, B Foss, S Skogestad
Computers & Chemical Engineering 136, 106765, 2020
A Primal decomposition algorithm for distributed multistage scenario model predictive control
D Krishnamoorthy, B Foss, S Skogestad
Journal of Process Control 81, 162-171, 2019
Changing between active constraint regions for optimal operation: Classical advanced control versus model predictive control
A Reyes-Lúa, C Zotică, T Das, D Krishnamoorthy, S Skogestad
Computer aided chemical engineering 43, 1015-1020, 2018
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