Blar i NTNU Open på forfatter "Krishnamoorthy, Dinesh"

A Distributed Algorithm for Scenariobased Model Predictive Control using Primal Decomposition *
Krishnamoorthy, Dinesh; Foss, Bjarne Anton; Skogestad, Sigurd (Journal article; Peer reviewed, 2018)In this paper, we consider the decomposition of scenariobased model predictive control problem. Scenario MPC explicitly considers the concept of recourse by representing the evolution of uncertainty by a discrete scenario ... 
A Distributed Optimization Strategy for Large Scale Oil and Gas Production Systems
Krishnamoorthy, Dinesh; Aguiar, Marco Aurelio; Foss, Bjarne Anton; Skogestad, Sigurd (Journal article; Peer reviewed, 2018)n this paper, we consider the problem of realtime optimization of an oil and gas production network. The production network is often made of several wells from different reservoir sections producing to a common processing ... 
A Dynamic Extremum Seeking Scheme Applied to Gas Lift Optimization
Krishnamoorthy, Dinesh; Ryu, Jeongrim; Skogestad, Sigurd (Journal article; Peer reviewed, 2019)This paper presents the application of a datadriven optimization scheme using transient measurements to a gaslift optimization problem. Optimal operation of a gaslifted field involves controlling the marginal gasoil ... 
A Primal decomposition algorithm for distributed multistage scenario model predictive control
Krishnamoorthy, Dinesh; Foss, Bjarne Anton; Skogestad, Sigurd (Journal article; Peer reviewed, 2019)This paper proposes a primal decomposition algorithm for efficient computation of multistage scenario model predictive control, where the future evolution of uncertainty is represented by a scenario tree. This often results ... 
Changing between Active Constraint Regions for Optimal Operation: Classical Advanced Control versus Model Predictive Control
ReyesLúa, Adriana; Zotica, Cristina Florina; Das, Tamal; Krishnamoorthy, Dinesh; Skogestad, Sigurd (Journal article; Peer reviewed, 2018)Control structures must be properly designed and implemented to maintain optimality. The two options for the supervisory control layer are Advanced Control Structures (ACS) and Model Predictive Control (MPC). To systematically ... 
Control of Steadystate Gradient of an Ammonia Reactor using Transient Measurements
Bonnowitz, Harro; Straus, Julian; Krishnamoorthy, Dinesh; Jahanshahi, Esmaeil; Skogestad, Sigurd (Journal article; Peer reviewed, 2018)This paper presents the application of a steadystate realtime optimization strategy using transient measurements to an ammonia synthesis reactor case. We apply a new method for estimating the steadystate gradient of the ... 
Datadriven Scenario Selection for Multistage Robust Model Predictive Control
Krishnamoorthy, Dinesh; Thombre, Mandar; Skogestad, Sigurd; Jäschke, Johannes (Journal article; Peer reviewed, 2018)A main assumption in many works considering multistage model predictive control (MPC) is that discrete realizations of the uncertainty are chosen apriori and that the scenario tree is given. In this work, we focus on ... 
Dynamic Extremum Seeking Control Using ARX model
Ryu, Jeongrim (Master thesis, 2018)In the design of the dynamic ESC, a wave perturbation is decided to be not a sinusoidal wave but a pseudorandom binary sequence(PRBS) wave. The reason behind this is that diverse frequencies in the PRBS wave make the ARX ... 
Fast Economic Model Predictive Control for a Gas Lifted Well Network
Suwartadi, Eka; Krishnamoorthy, Dinesh; Jaeschke, Johannes (Journal article; Peer reviewed, 2018)This paper considers the optimal operation of an oil and gas production network by formulating it as an economic nonlinear model predictive control (NMPC) problem. Solving the associated nonlinear program (NLP) can be ... 
Feedback RealTime Optimization Strategy Using a Novel Steadystate Gradient Estimate and Transient Measurements
Krishnamoorthy, Dinesh; Jahanshahi, Esmaeil; Skogestad, Sigurd (Journal article; Peer reviewed, 2019)This paper presents a new feedback realtime optimization (RTO) strategy for steadystate optimization that directly uses transient measurements. The proposed RTO scheme is based on controlling the estimated steadystate ... 
Gaslift Optimization by Controlling Marginal GasOil Ratio using Transient Measurements
Krishnamoorthy, Dinesh; Jahanshahi, Esmaeil; Skogestad, Sigurd (Journal article; Peer reviewed, 2018)This paper presents the application of a steadystate gradient control using transient measurements to a gaslift optimization problem. Optimal operation of a gaslifted field involves controlling the marginal gasoil ratio ... 
Improving Scenario Decomposition for Multistage MPC using a Sensitivitybased Pathfollowing Algorithm
Krishnamoorthy, Dinesh; Suwartadi, Eka; Foss, Bjarne Anton; Skogestad, Sigurd; Jäschke, Johannes (Journal article; Peer reviewed, 2018)This letter proposes a computationally efficient algorithm for robust multistage scenario model predictive control (MPC). In multistage scenario MPC, the evolution of uncertainty in the prediction horizon is represented ... 
Lagrangian Decomposition for Dynamic RealTime Optimization: Applied to Production Optimization Network
Sørlie, Ingvild (Master thesis, 2017)The scope of this thesis was to investigate the use of lagrangian decomposition for a dynamic realtime optimization(RTO) problem. The decomposition was performed on a gas lifted twowell network, controlled by a nonlinear ... 
Novel Approaches to Online Process Optimization Under Uncertainty: Addressing the limitations of current industrial practice
Krishnamoorthy, Dinesh (Doctoral theses at NTNU;2019:301, Doctoral thesis, 2019)In the face of growing competition and increased necessity to focus on sustainability and energy efficiency, there is a clear need to optimize the daytoday operation of many industrial processes. This involves online ... 
Online Process Optimization with Active Constraint Set Changes using Simple Control Structures
Krishnamoorthy, Dinesh; Skogestad, Sigurd (Journal article; Peer reviewed, 2019)The purpose of this paper is to show that online process optimization can be achieved using simple control structures without the need for solving numerical optimization problems online. In particular, we show that changes ... 
RealTime Optimization under Uncertainty Applied to a Gas Lifted Well Network
Krishnamoorthy, Dinesh; Foss, Bjarne Anton; Skogestad, Sigurd (Journal article; Peer reviewed, 2016)In this work, we consider the problem of daily production optimization in the upstream oil and gas domain. The objective is to find the optimal decision variables that utilize the production systems efficiently and maximize ... 
Slug handling with a virtual harp based on nonlinear predictive control for a gravity separator
Backi, Christoph Josef; Krishnamoorthy, Dinesh; Skogestad, Sigurd (Journal article; Peer reviewed, 2018)This paper presents a nonlinear model predictive control approach for a threephase gravity separator model. The aim of the controller is to dampen sluginduced, oscillatory disturbances in the inflow to the gravity ... 
SteadyState Realtime Optimization using Transient Measurements
Krishnamoorthy, Dinesh; Foss, Bjarne Anton; Skogestad, Sigurd (Journal article; Peer reviewed, 2018)Realtime optimization (RTO) is an established technology, where the process economics are optimized using rigourous steadystate models. However, a fundamental limiting factor of current static RTO implementation is the ...