Model predictive control of a laboratory gas turbine

Surendran, Swathi; Chandrawanshi, Ritesh; Kulkarni, Sumeet; Bhartiya, Sharad; Nataraj, P. S. V.; Sampath, Suresh

doi:10.1109/indiancc.2016.7441109

Cited by 15 publications

(6 citation statements)

References 7 publications

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“…The guidelines required for Modelling of GT is provided in [8,[21][22][23][24]. Also, experimental empirical transfer function models for gas turbines (GT) can be done [17].…”

Section: Model Descriptionmentioning

confidence: 99%

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Study on the Impact of Turbine Controls on Transient Stability of Synchronous Machine

Menon

Babu

Desabhatla

2016

JGE

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This article discusses the work carried out in the development, validation and verification of the Turbine/Governor model (GGOV1) in GE Control Systems Toolbox to comprehend the impact of Turbine controls post system transient. Simulation related studies are carried out using the model developed. MATLAB /Simulink has been used as the platform for validating the model. The validated model is replicated in the GE Control System Toolbox , for enhanced grid Simulation related studies. Comparative analysis of results obtained in both platforms with the validated parameters has been accomplished.

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“…The guidelines required for Modelling of GT is provided in [8,[21][22][23][24]. Also, experimental empirical transfer function models for gas turbines (GT) can be done [17].…”

Section: Model Descriptionmentioning

confidence: 99%

“…The validated parameters of 7F Gas Turbine [16][17][18][19][20] used in the GGOV1 MATLAB /Simulink model, for implementing the model in the GE Control Systems Toolbox are listed in the following table:…”

Section: Parameter Validation For 7f Gas Turbinesmentioning

confidence: 99%

Study on the Impact of Turbine Controls on Transient Stability of Synchronous Machine

Menon

Babu

Desabhatla

2016

JGE

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“…However, the simulation was only carried around the nominal conditions. 11 In the study by Seok et al, 12 the linear state-space model of the gas turbine was identified from the input–output data of the nonlinear model near a nominal operating point, then the rate-based MPC controller was designed. Although linear MPC can be effectively solved during the optimization phase, it would lead to poor closed-loop performance when the gas turbine operates far from the nominal operating point.…”

Section: Introductionmentioning

confidence: 99%

Model predictive control for gas turbine shaft speed based on model compensation using extended state observer

Zhang

Xue

Wei

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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Gas turbine engines have offered advanced power generation with relatively small size on marine vessels. The operational flexibility has high control requirements for shaft speed regulation. Model predictive control provides a methodology for safe and efficient operation of gas turbines. However, when working at partial load, the controller degrades due to the mismatch between predictive model in model predictive control and dynamics of gas turbine. To deal with the issue of model adaptability in model predictive control, model compensation–based model predictive control is proposed for the gas turbine operation. The dynamics of the plant is modified by the extended state observer to get close to the pure integrator. The model predictive control is devised based on the modified plant. The wide-range load regulation and disturbance rejection of gas turbine have been improved by leveraging the benefits of model compensation–based model predictive control.

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“…For instance, H ∞ synthesis algorithms [7], single neural adaptive propositional-integral-derivative PID controllers [8] and non-linear controllers based on a linear control-loop with an exogenous non-linearity [4] have been developed to handle the process non-linearities. On the other hand, model uncertainty has been handled through model predictive control in [9,10]. Control schemes focused on disturbance rejection have also been developed, such as those based on local optimum PID controllers [11] and those based on Active Disturbance Rejection Control ADRC schemes [12].…”

Section: Introductionmentioning

confidence: 99%

Turbojet Thrust Augmentation through a Variable Exhaust Nozzle with Active Disturbance Rejection Control

Villarreal-Valderrama

Zambrano‐Robledo

Hernández-Alcantara

et al. 2021

Aerospace

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Turbojets require variable exhaust nozzles to fit high-demanding applications; however, few reports on nozzle control are available. The purpose of this paper is to investigate the possible advantages of an exhaust gas control through a variable exhaust nozzle. The control design method combines successful linear active disturbance rejection control (LADRC) capabilities with a loop shaping controller (LSC) to: (i) allow designing the closed-loop characteristics in terms of gain margin, phase margin and bandwidth, and (ii) increase the LSC disturbance rejection capabilities with an extended state observer. A representation of the nozzle dynamics is obtained from first principles and adapted to achieve a stream-velocity-based control loop. The results show that the resulting controller allows improving the expansion of the exhaust gas to the ambient pressure for the whole operating range of the turbojet, increasing the estimated thrust by 14.23% during the tests with experimental data.

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Model predictive control of a laboratory gas turbine

Cited by 15 publications

References 7 publications

Study on the Impact of Turbine Controls on Transient Stability of Synchronous Machine

Study on the Impact of Turbine Controls on Transient Stability of Synchronous Machine

Model predictive control for gas turbine shaft speed based on model compensation using extended state observer

Turbojet Thrust Augmentation through a Variable Exhaust Nozzle with Active Disturbance Rejection Control

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