Markov modelling for energy efficient control of gas turbine power plant

Куликов, Г.Г.; Arkov, V.Y.; Abdulnagimov, Ansaf

doi:10.3182/20100329-3-pt-3006.00014

Cited by 7 publications

(2 citation statements)

References 1 publication

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“…The estimation of a transition probability matrix of the Markov model consists of creation of multidimensional histograms which represent an estimate of joint distribution [14,15].…”

Section: Elements Unitsmentioning

confidence: 99%

System Safety of Gas Turbines: Hierarchical Fuzzy Markov Modelling

Куликов¹,

Arkov²,

Abdulnagimov³

2013

Progress in Gas Turbine Performance

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“…The estimation of a transition probability matrix of the Markov model consists of creation of multidimensional histograms which represent an estimate of joint distribution [14,15].…”

Section: Elements Unitsmentioning

confidence: 99%

System Safety of Gas Turbines: Hierarchical Fuzzy Markov Modelling

Куликов¹,

Arkov²,

Abdulnagimov³

2013

Progress in Gas Turbine Performance

Self Cite

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“…The detailed description can be found in [5,6]. At various stages of the lifecycle of the control system, models of varying complexity are used: Element-by-element [13], multiregime [14], and point models [15].…”

Section: Introductionmentioning

confidence: 99%

Design of Nonlinear Control of Gas Turbine Engine Based on Constant Eigenvectors

Valeev

Kondratyeva

2021

Machines

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A gas turbine engine represents a complex dynamic control object. Its characteristics change depending on the state of the environment and the regimes of its operation. This paper discusses an algorithmic approach to the design of a nonlinear controller, based on the concept of constant eigenvectors and analytical design of the control system. The proposed design method makes it possible to ensure the stability and the required quality of transient processes at different acceleration modes. In this case, the constancy of the matrix of the canonical basis of the closed-loop control system is assumed, which guarantees stability. The design of a neural network dynamic model of a gas turbine engine based on a neural network approximator with one input and multiple outputs is considered. An example of the design of a nonlinear controller for a gas turbine engine is considered, the neural network model of which is given in the state space. The application of neural network approximation of controller coefficients is presented.

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Probabilistic graphical models in energy systems: A review

Zhao

Yan

et al. 2021

Build. Simul.

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Markov modelling for energy efficient control of gas turbine power plant

Cited by 7 publications

References 1 publication

System Safety of Gas Turbines: Hierarchical Fuzzy Markov Modelling

System Safety of Gas Turbines: Hierarchical Fuzzy Markov Modelling

Design of Nonlinear Control of Gas Turbine Engine Based on Constant Eigenvectors

Probabilistic graphical models in energy systems: A review

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