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A new calibration algorithms of spinning projectile aerodynamic parameters

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Journal of Harbin Institute of Technology(New Series) 2005年第4期12卷 440-445页

作者：丛明煜张伟王丽萍 School of Astronautics Harbin Institute of Technology Harbin 150001 China

This paper demonstrates that the application of calibration algorithms of aerodynamic parameters for the trajectory of spinning projectile is successful. First, from the point of view of the trajectory simulation, a general summary of well-known trajectory models is given. A five degrees of freedom （5 DOF） model is developed that can match the projectile motion essentially in the vertex region, and the results obtained by 5 DOF model are in close agreement with those of a more sophisticated 6 DOF model for elevation angles above 45 degrees. Secondly, the calibration algorithms have been developed and are summarized. The methods of calibrating the flight trajectory models are compared, and these methods are shown to be effective in the representative cases. In addition, the method of Math number calibration （MNC） is presented; some possible areas in MNC for further investigation are indicated together with benefits to be gained. The utilization of MNC schemes not only allow a worthwhile reduction of calibration rounds firing in range and accuracy （R＆A） trial and production of firing tables （PFT） test, but also make PFT and fire control data （FCD） more cost effective.

关键词： trajectory models trajectory simulation spinning projectile aerodynamic parameters calibration algorithms

DETERMINATION OF aerodynamic parameters OF CROP CANOPIES WITH A CENTER-OF-PRESSURE METHOD

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Acta meteorologica Sinica 1995年第1期9卷 78-86页

作者：覃文汉 Laboratory for Eco-Environmental Physics Institute of GeographyChinese Academy of SciencesBeijing 100101

Using data on leaf area density and wind profiles above and within canopies of wheat,rice,soybean and corn,the center-of-pressure method (CPM),originally proposed by Thom (1971),is first validated in the field.A physically-based model for directly calculating zero-displacement height (d) is *** comparison between the friction velocity (u_*) estimated with CPM and that with eddy correlation technique shows that CPM not only works well in the field,but also produces more steady and accurate estimates of aerodynamic parameters (which are hardly affected by atmospheric thermal stability),than those with the widely-used log-profile fitting method in diabatic atmosphere. The results presented in this paper also demonstrate that the ratios of d,z_0 to crop height h usually vary with canopy ar- chitecture,atmospheric stratification and turbulent exchange intensity,and are not just constants as commonly assumed or used.d/h raises with an increase of relative height of the maximum foliage layer and wind extinction coefficient within the *** for crops with short stem and moderate foliage density,can the relations d= 0.64h,z_0=0.08h keep *** addition,for long stem crops or sparse canopies,the fairly large shear stress at the soil surface and the va- riation of the exponent in the relationship between drag coefficient and wind speed undoubtedly influence the accuracy of CPM to a certain extent.

关键词： aerodynamic parameters crop canopy center-of-pressure method(CPM) Yucheng Comprehensive Experimental Station

Longitudinal parameter identification of a small unmanned aerial vehicle based on modified particle swarm optimization

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Chinese Journal of Aeronautics 2015年第3期28卷 865-873页

作者： Jiang Tieying Li Jie Huang Kewei College of Mechanical and Electrical Engineering Beijing Institute of Technology

Abstract This paper describes a longitudinal parameter identification procedure for a small unmanned aerial vehicle （UAV） through modified particle swam optimization （PSO）. The proce- dure is demonstrated using a small UAV equipped with only an micro-electro-mechanical systems （MEMS） inertial mea,mring element and a global positioning system （GPS） receiver to provide test information. A small UAV longitudinal parameter mathematical model is derived and the modified method is proposed based on PSO with selective particle regeneration （SRPSO）. Once modified PSO is applied to the mathematical model, the simulation results show that the mathematical model is correct, and aerodynamic parameters and coefficients of the propeller can be identified accurately. Results are compared with those of PSO and SRPSO and the comparison shows that the proposed method is more robust and faster than the other methods for the longitudinal parameter identification of the small UAV. Some parameter identification results are affected slightly by noise, but the identification results are very good overall. Eventually, experimental validation is employed to test the proposed method, which demonstrates the usefulness of this method.

关键词： aerodynamic parameters Local optimization Parameter identification Particle swarm optimization(PSO) Small unmanned aerialvehicle

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

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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)*** 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 *** LM method combines the already-trained LSTM network model to optimize the unknown aerodynamic *** 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

Parameter Identification of Hypersonic Vehicle Based on LSTM Algorithm

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Parameter Identification of Hypersonic Vehicle Based on LSTM...