Aeroengine Robust Gain-Scheduling Control Based on Performance Degradation

Gou, Linfeng; Liu, Zhidan; Ding, Fan; Zheng, Hairong

doi:10.1109/access.2020.2986336

Cited by 13 publications

(5 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, the onboard engine model with health parameters is represented as piecewise linearized Kalman filters. Then, H-infinity control theory is used for controller design to achieve good reference tracking with robustness and stability [81]. The H-infinity output tracking problem for aero-engines with a model representation of switched linear-parametervarying (LPV) systems is also investigated.…”

Section: Robust Controlmentioning

confidence: 99%

Sustainable Aviation Electrification: A Comprehensive Review of Electric Propulsion System Architectures, Energy Management, and Control

2022

View full text Add to dashboard Cite

The civil aviation sector plays an increasingly significant role in transportation sustainability in the environmental, economic, and social dimensions. Driven by the concerns of sustainability in the aviation sector, more electrified aircraft propulsion technologies have emerged and form a very promising approach to future sustainable and decarbonized aviation. This review paper aims to provide a comprehensive and broad-scope survey of the recent progress and development trends in sustainable aviation electrification. Firstly, the architectures of electrified aircraft propulsion are presented with a detailed analysis of the benefits, challenges, and studies/applications to date. Then, the challenges and technical barriers of electrified aircraft propulsion control system design are discussed, followed by a summary of the control methods frequently used in aircraft propulsion systems. Next, the mainstream energy management strategies are investigated and further utilized to minimize the block fuel burn, emissions, and economic cost. Finally, an overview of the development trends of aviation electrification is provided.

show abstract

Section: Robust Controlmentioning

confidence: 99%

Sustainable Aviation Electrification: A Comprehensive Review of Electric Propulsion System Architectures, Energy Management, and Control

2022

View full text Add to dashboard Cite

show abstract

“…It should be noted that 18 records [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35] that are directly related to the subject were obtained from the Scopus database in this section, and the results are reviewed in what follows. The most frequent words of this section are listed in Table 2, indicating that the research on this subject has been conducted on aero-engines and, in particular, turbofan engines.…”

Section: Analysis and Evaluationmentioning

confidence: 99%

Compressor Degradation Management Strategies for Gas Turbine Aero-Engine Controller Design

et al. 2021

View full text Add to dashboard Cite

The Advisory Council for Aeronautics Research in Europe (ACARE) Flight Path 2050 focuses on ambitious and severe targets for the next generation of air travel systems (e.g., 75% reduction in CO2 emissions per passenger kilometre, a 90% reduction in NOx emissions, and a 65% reduction in the noise emissions of flying aircraft relative to the capabilities of typical new aircraft in 2000). Degradation is an inevitable phenomenon as aero-engines age with significant impacts on the engine performance, emissions level, and fuel consumption. The engine control system is a key element capable of coping with degradation consequences subject to the implementation of an advanced management strategy. This paper demonstrates a methodological approach for aero-engine controller adjustment to deal with degradation implications, such as emission levels and increased fuel consumption. For this purpose, a component level model for an aero-engine was first built and transformed to a block-structured Wiener model using a system identification approach. An industrial Min-Max control strategy was then developed to satisfy the steady state and transient limit protection requirements simultaneously while satisfying the physical limitation control modes, such as over-speed, surge, and over-temperature. Next, the effects of degradation on the engine performance and associated changes to the controller were analysed thoroughly to propose practical degradation management strategies based on a comprehensive scientometric analysis of the topic. The simulation results show that the proposed strategy was effective in restoring the degraded engine performance to the level of the clean engine while protecting the engine from physical limitations. The proposed adjustments in the control strategy reduced the fuel consumption and, as a result, the emission level and carbon footprint of the engine.

show abstract

“…Though, most of these methods are for linear models. Then scholars also proposed nonlinear control methods such as gain scheduling control [4,17], model predictive control [16], and sliding mode variable structure control [11] on this basis. All of these control methods require the establishment of a comparatively precise system model and design of accurate controller with the foundation.…”

Section: Introductionmentioning

confidence: 99%

Design of Intelligent Controller for Aero-engine Based on TD3 Algorithm

Zhu,

Tang,

Dong

2023

ITC

View full text Add to dashboard Cite

Recently, higher structure complicacy and performances requirements of the aero-engine have brought higher demands on its control system. For the control of aerodynamic thermodynamic system, the intelligent control method with self-learning ability will be a promising choice. In the paper, we propose an aero-engine intelligent controller design method based on twin delayed deep deterministic policy gradient (TD3) algorithm. The method enables the intelligent controller to learn continuously according to the feedback of the environment and control the aero-engine. The paper takes the intelligent controller design of the JT9D turbofan engine as an example. First, the aero-engine control problem is described as a Markov decision process for deep reinforcement learning algorithms. Second, a complete intelligent controller design process is constructed by reasonably designing the network structure and reward function. Finally, the comparison simulations are conducted to verify the effectiveness of the proposed methods. The simulation results show that the TD3 controller outperforms deep deterministic policy gradient (DDPG) and the proportional-integral-derivative (PID) in the aero-engine control task. And the TD3 controller can realize the tracking control of low-pressure turbine speed with quick response and small overshoot.

show abstract

Aeroengine Robust Gain-Scheduling Control Based on Performance Degradation

Cited by 13 publications

References 45 publications

Sustainable Aviation Electrification: A Comprehensive Review of Electric Propulsion System Architectures, Energy Management, and Control

Sustainable Aviation Electrification: A Comprehensive Review of Electric Propulsion System Architectures, Energy Management, and Control

Compressor Degradation Management Strategies for Gas Turbine Aero-Engine Controller Design

Design of Intelligent Controller for Aero-engine Based on TD3 Algorithm

Contact Info

Product

Resources

About