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Aircraft parameter estimation using a stacked long short-term memory network and Levenberg-Marquardt method

Chinese Journal of Aeronautics 2024年第2期37卷 123-136页

作者： Zhe HUI Yinan KONG Weigang YAO Gang CHEN School of Aerospace Science and Technology Xidian UniversityXi’an 710071China Computation Aerodynamics Institution China Aerodynamics Research and Development CenterMianyang 621000China Faculty of Computing Engineering and MediaDe Montfort UniversityLeicester LE19BHUnited Kingdom School of Aerospace Engineering Xi’an Jiaotong UniversityXi’an 710049China

To effectively estimate the unknown aerodynamic parameters from the aircraft’s flight data,this paper proposes a novel aerodynamic parameter estimation method incorporating a stacked Long Short-Term Memory(LSTM)network model and the Levenberg-Marquardt(LM)method.The stacked LSTM network model was designed to realize the aircraft dynamics modeling by utilizing a frame of nonlinear functional mapping based entirely on the measured input-output data of the aircraft system without requiring explicit postulation of the dynamics.The LM method combines the already-trained LSTM network model to optimize the unknown aerodynamic parameters.The proposed method is applied by using the real flight data,generated by ATTAS aircraft and a bio-inspired morphing Unmanned Aerial Vehicle(UAV).The investigation reveals that for the two different flight data,the designed stacked LSTM network structure can maintain the efficacy of the network prediction capability only by appropriately adjusting the dropout rates of its hidden layers without changing other network parameters(i.e.,the initial weights,initial biases,number of hidden cells,time-steps,learning rate,and number of training iterations).Besides,the proposed method’s effectiveness and potential are demonstrated by comparing the estimated results of the ATTAS aircraft or the bio-inspired morphing UAV with the corresponding reference values or wind-tunnel results.

关键词： Parameter estimation LSTM network model LM method Aerodynamic parameters flight data Aircraft dynamics modeling Network prediction capability Network parameters

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A survey of unmanned aerial vehicle flight data anomaly detection:Technologies,applications,and future directions

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Science China(Technological Sciences) 2023年第4期66卷 901-919页

作者： YANG Lei LI ShaoBo LI ChuanJiang ZHANG AnSi ZHANG XuDong School of Mechanical Engineering Guizhou UniversityGuiyang 550025China State Key Laboratory of Public Big data Guizhou UniversityGuiyang 550025China

flight data anomaly detection plays an imperative role in the safety and maintenance of unmanned aerial vehicles(UAVs).It has attracted extensive attention from researchers.However,the problems related to the difficulty in obtaining abnormal data,low model accuracy,and high calculation cost have led to severe challenges with respect to its practical applications.Hence,in this study,firstly,several UAV flight data simulation softwares are presented based on a brief presentation of the basic concepts of anomalies,the contents of UAV flight data,and the public datasets for flight data anomaly detection.Then,anomaly detection technologies for UAV flight data are comprehensively reviewed,including knowledge-based,model-based,and data-driven methods.Next,UAV flight data anomaly detection applications are briefly described and analyzed.Finally,the future trends and directions of UAV flight data anomaly detection are summarized and prospected,which aims to provide references for the following research.

关键词： unmanned aerial vehicle(UAV) flight data anomaly detection data-driven

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Aerodynamic design,analysis,and validation techniques for the Tianwen-1 entry module

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Astrodynamics 2022年第1期6卷 39-52页

作者： Qi Li Wei Rao Xiaoli Cheng Haogong Wei Chuang Wang Jie Dong Beijing Space Vehicle Design Department China Academy of Space TechnologyBeijing 100094China China Academy of Aerospace and Aerodynamics Beijing 100074China

The clear differences between the atmosphere of Mars and the Earth coupled with the lack of a domestic research basis were significant challenges for the aerodynamic prediction and verification of Tianwen-1.In addition,the Mars entry,descent,and landing(EDL)mission led to specific requirements for the accuracy of the aerodynamic deceleration performance,stability,aerothermal heating,and various complex aerodynamic coupling problems of the entry module.This study analyzes the key and difficult aerodynamic and aerothermodynamic problems related to the Mars EDL process.Then,the study process and results of the design and optimization of the entry module configuration are presented along with the calculations and experiments used to obtain the aerodynamic and aerothermodynamic characteristics in the Martian atmosphere.In addition,the simulation and verification of the low-frequency free oscillation characteristics under a large separation flow are described,and some special aerodynamic coupling problems such as the aeroelastic buffeting response of the trim tab are discussed.Finally,the atmospheric parameters and aerodynamic characteristics obtained from the flight data of the Tianwen-1 entry module are compared with the design data.The data obtained from the aerodynamic design,analysis,and verification of the Tianwen-1 entry module all meet the engineering requirements.In particular,the flight data results for the atmospheric parameters,trim angles of attack,and trim axial forces are within the envelopes of the prediction deviation zones.

关键词： Mars entry,descent,and landing(EDL) design and optimization of the entry module configuration calculations and experiments of aerodynamic and aerothermodynamic characteristics low-frequency free oscillation under large separation flow special aerodynamic coupling problems flight data

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Symbol Method for Fast Similarity Search in Large Time Series flight databases

Symbol Method for Fast Similarity Search in Large Time Serie...

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2012 International Conference on Convergence Computer Technology(IC3T 2012)

作者： Yang Hui Zhang Guozhen Dept.of Computer Science ＆ Technology Civil Aviation of China

Taking into account the status of airline maintenance and the characteristics of time series search,we use a symbolic representation called Symbolic Aggregate Approximation to section the flight data linearity and then discrete them into a sequence of characters.The data which needs specific analysis should be retained.According to that,an index tree of query sequence for fast similarity search could be set to ensure that there are no omissions left.When we do similarity search on the sequence transformed flight data,the fault models provided by experts are regarded as the standards so that the causes of the malfunctions can be fixed and the suggestions for maintenance can be offered.We use actual flying data to validate this algorithm.The efficiency and the simplicity of it have been proved.

关键词： Symbolic transform Similarity flight data

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