Comparison of model predictive controller and optimized min-max algorithm for turbofan engine fuel control

Montazeri-Gh, Morteza; Rasti, Ali

doi:10.1007/s12206-019-0847-3

Cited by 6 publications

(4 citation statements)

References 32 publications

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“…Humpback whales engage in synchronized swimming around their prey, following a spiral-shaped trajectory as described by (11). During the exploitation phase, the search agent's position is modified based on a search agent that is randomly selected, as described by ( 12) and (13).…”

Section: Woamentioning

confidence: 99%

“…𝑋 (𝑡 + 1) = 𝑋 𝑟𝑎𝑛𝑑 − 𝐴. ⃗⃗⃗ 𝐷 ⃗ ⃗ (13) where 𝑋 𝑟𝑎𝑛𝑑 is a random position vector chosen from the current population.…”

Section: 𝑋 (𝑡mentioning

confidence: 99%

“…Wei et al [12] presented model-based method, namely A self-enhancing active transient protection (SeATP), to handle the limit of surge margin and turbine inlet temperature. Montazeri-Gh and Rasti [13] employed the GA to tune the min-max algorithm and model predictive control of the turbofan engine. Pang et al [14] proposed direct thrust control based on an improved model predictive control using a certain strategy that reduced the control sequence dimension.…”

Section: Introductionmentioning

confidence: 99%

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Control system optimisation of biodiesel-based gas turbine for ship propulsion

Machmudah,

Bakar,

et al. 2024

IJ-AI

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<p>Reducing a gas emission of shipping transportations become a main goal of international maritime organization to achieve a clean energy. One of best scenarios to achieve this goal is to shift a fossil fuel to a renewable energy-based fuel of a ship propulsion. This paper studies an optimization of a control system of the renewable-based small gas turbine engine for the ship propulsion. Proposed control system consists of a proportional-integral with engine performance limiters to avoid an engine damage. Proportional-integral gains are tuned by a whale optimization algorithm. A gain scheduling analysis of a step response is performed to obtain a searching area of tuning parameters and values of constant gains. In this step, the gains are modeled as function of plant variables. After the searching area is obtained, the proportional-integral gains are optimized using the whale optimization algorithm while the additional gains are set as constant values. Using this scenario, stable and optimal gains have been successfully achieved. Results show that the proposed method has better performance than that of the previous methods, i.e. gain scheduling and gain scheduling optimized by the whale optimization algorithm. The proposed method has lowest fitness value and does not have an overshoot problem.</p>

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Section: Woamentioning

confidence: 99%

“…𝑋 (𝑡 + 1) = 𝑋 𝑟𝑎𝑛𝑑 − 𝐴. ⃗⃗⃗ 𝐷 ⃗ ⃗ (13) where 𝑋 𝑟𝑎𝑛𝑑 is a random position vector chosen from the current population.…”

Section: 𝑋 (𝑡mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Control system optimisation of biodiesel-based gas turbine for ship propulsion

Machmudah,

Bakar,

et al. 2024

IJ-AI

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“…In Table 2, scientometric survey data in the Histcite are shown. As shown in Table 2, the number of articles reviewed in scientometrics is 111, 12…”

Section: Bibliometric and Scientometric Analysismentioning

confidence: 99%

A scientometric analysis and critical review of gas turbine aero-engines control: From Whittle engine to more-electric propulsion

Mohammadi

Fashandi

Jafari

et al. 2020

Measurement and Control

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The gas turbine aero-engine control systems over the past eight decades have been thoroughly investigated. This review purposes are to present a comprehensive reference for aero-engine control design and development based on a systematic scientometric analysis and to categorize different methods, algorithms, and approaches taken into account to improve the performance and operability of aircraft engines from the first days to present to enable this challenging technology to be adopted by aero-engine manufacturers. Initially, the benefits of the control systems are restated in terms of improved engine efficiency, reduced carbon dioxide emissions, and improved fuel economy. This is followed by a historical coverage of the proposed concepts dating back to 1936. A comprehensive scientometric analysis is then presented to introduce the main milestones in aero-engines control. Possible control strategies and concepts are classified into four distinct phases, including Single input- single output control algorithms, MIN-MAX or Cascade control algorithms, advanced control algorithms, More-electric and electronic control algorithms and critically reviewed. The advantages and disadvantages of milestones are discussed to cover all practical aspects of the review to enable the researchers to identify the current challenges in aircraft engine control systems.

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