Subspace identification for disturbance rejection control design in gas turbines

Holcomb, Chad M.; Callafon, Raymond de

doi:10.1109/ecc.2015.7330647

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…Figures [13][14][15][16] show the drift fault estimated by the proposed L 1 -norm LBO. Moreover, Figures 17-20 illustrate fault estimation for stuck fault which is similar to a temporary bias.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…12,13 Data-driven models have been developed for tolerating the disadvantages of classical models. 14,15 However, data-driven models require expertise experiences, knowledge on thermodynamics and physics to cover whole aspects of real-world problems. 16 The mathematical GT modeling was extremely used in control of system development, design, and test.…”

Section: Introductionmentioning

confidence: 99%

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Development of L₁-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine

Akbari

Khoshnood

Irani

2021

Proceedings of the Institution of Mechanical Engineers, Part I:

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In this article, a novel approach for model-based sensor fault detection and estimation of gas turbine is presented. The proposed method includes driving a state-space model of gas turbine, designing a novel L1-norm Lyapunov-based observer, and a decision logic which is based on bank of observers. The novel observer is designed using multiple Lyapunov functions based on L1-norm, reducing the estimation noise while increasing the accuracy. The L1-norm observer is similar to sliding mode observer in switching time. The proposed observer also acts as a low-pass filter, subsequently reducing estimation chattering. Since a bank of observers is required in model-based sensor fault detection, a bank of L1-norm observers is designed in this article. Corresponding to the use of the bank of observers, a two-step fault detection decision logic is developed. Furthermore, the proposed state-space model is a hybrid data-driven model which is divided into two models for steady-state and transient conditions, according to the nature of the gas turbine. The model is developed by applying a subspace algorithm to the real field data of SGT-600 (an industrial gas turbine). The proposed model was validated by applying to two other similar gas turbines with different ambient and operational conditions. The results of the proposed approach implementation demonstrate precise gas turbine sensor fault detection and estimation.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development of L₁-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine

Akbari

Khoshnood

Irani

2021

Proceedings of the Institution of Mechanical Engineers, Part I:

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Experimental Identification of a Car Dynamic Model Using the Numerical Algorithms for Subspace State-Space System Identification

Lettieri

Pappalardo

2020

Advances in Design, Simulation and Manufacturing III

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Progress in Modeling and Control of Gas Turbine Power Generation Systems: A Survey

Mohamed

Khalil

2020

Energies

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This paper reviews the modeling techniques and control strategies applied to gas turbine power generation plants. Recent modeling philosophies are discussed and the state-of-the-art feasible strategies for control are shown. Research conducted in the field of modeling, simulation, and control of gas turbine power plants has led to notable advancements in gas turbines’ operation and energy efficiency. Tracking recent achievements and trends that have been made is essential for further development and future research. A comprehensive survey is presented here that covers the outdated attempts toward the up-to-date techniques with emphasis on different issues and turbines’ characteristics. Critical review of the various published methodologies is very useful in showing the importance of this research area in practical and technical terms. The different modeling approaches are classified and each category is individually investigated by reviewing a considerable number of research articles. Then, the main features of each category or approach is reported. The modern multi-variable control strategies that have been published for gas turbines are also reviewed. Moreover, future trends are proposed as recommendations for planned research.

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Subspace identification for disturbance rejection control design in gas turbines

Cited by 3 publications

References 11 publications

Development of L₁-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine

Development of L₁-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine

Experimental Identification of a Car Dynamic Model Using the Numerical Algorithms for Subspace State-Space System Identification

Progress in Modeling and Control of Gas Turbine Power Generation Systems: A Survey

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Subspace identification for disturbance rejection control design in gas turbines

Cited by 3 publications

References 11 publications

Development of L1-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine

Development of L1-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine

Experimental Identification of a Car Dynamic Model Using the Numerical Algorithms for Subspace State-Space System Identification

Progress in Modeling and Control of Gas Turbine Power Generation Systems: A Survey

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Development of L₁-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine

Development of L₁-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine