Research on the control method of turbine outlet temperature limitation protection based on nonlinear state estimation

Abstract Developing multivariable control schedules for turboshaft engines addresses critical safety demands in aero-engine performance. This study introduces a turbine outlet temperature (TOT) limitation protection method using nonlinear state estimation. A turboshaft engine multivariable controller is designed, complemented by a Bidirectional Long Short-Term Memory (BLSTM) network-based onboard model. Validation shows less than 2 % relative error between the BLSTM model and the component-level engine model. To enhance precision, an Unscented Kalman State Estimator (UKSE) leverages residuals from power turbine speed data to estimate TOT (parameter T45), achieving a 1.4 % estimation error. The UKSE framework enables proactive temperature limitation control by dynamically adjusting protection thresholds. Experimental tests under two flight conditions confirm the method’s efficacy: 1) TOT exceedance magnitude decreases by 75 %, 2) overtemperature duration shortens by over 50 %, and 3) temperature violations are fully eliminated in specific scenarios. These results highlight the integration of BLSTM modeling and UKSE-based estimation as a robust strategy for mitigating turbine thermal risks while maintaining operational stability. The approach bridges model-based control and real-time adaptive protection, offering a scalable solution for next-generation engine safety systems.

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Publication Details

Journal
International Journal of Turbo and Jet Engines
Published
2026-01-08
DOI
https://doi.org/10.1515/tjj-2025-0059
Primary Topic
Turbomachinery Performance and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on the control method of turbine outlet temperature limitation protection based on nonlinear state estimation

Yuan Liu, W. Li, Bingxiong YIN, J. WU et al.
International Journal of Turbo and Jet Engines
Turbomachinery Performance and Optimization
article

Research on the control method of turbine outlet temperature limitation protection based on nonlinear state estimation

Yuan Liu, W. Li, Bingxiong YIN, J. WU, Qiuying Yan, Rui Tan, Hui Fang
article en

Abstract

Abstract Developing multivariable control schedules for turboshaft engines addresses critical safety demands in aero-engine performance. This study introduces a turbine outlet temperature (TOT) limitation protection method using nonlinear state estimation. A turboshaft engine multivariable controller is designed, complemented by a Bidirectional Long Short-Term Memory (BLSTM) network-based onboard model. Validation shows less than 2 % relative error between the BLSTM model and the component-level engine model. To enhance precision, an Unscented Kalman State Estimator (UKSE) leverages residuals from power turbine speed data to estimate TOT (parameter T45), achieving a 1.4 % estimation error. The UKSE framework enables proactive temperature limitation control by dynamically adjusting protection thresholds. Experimental tests under two flight conditions confirm the method’s efficacy: 1) TOT exceedance magnitude decreases by 75 %, 2) overtemperature duration shortens by over 50 %, and 3) temperature violations are fully eliminated in specific scenarios. These results highlight the integration of BLSTM modeling and UKSE-based estimation as a robust strategy for mitigating turbine thermal risks while maintaining operational stability. The approach bridges model-based control and real-time adaptive protection, offering a scalable solution for next-generation engine safety systems.

International Journal of Turbo and Jet Engines
Aviation Industry Corporation of China (China) (CN), Aero Engine Corporation of China (China) (CN), Tsinghua University (CN)
Affordable and clean energy
Openalex Percentile: Top 95%
Turbomachinery Performance and Optimization
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Research on the control method of turbine outlet temperature limitation protection based on nonlinear state estimation — Yuan Liu, W. Li, et al. · International Journal of Turbo and Jet Engines (2026) | TGRS Research Map | TGRS