Article of the Year 2020
Processing Technology Based on Radar Signal Design and ClassificationRead the full article
International Journal of Aerospace Engineering serves the international aerospace engineering community through the dissemination of scientific knowledge on practical engineering and design methodologies pertaining to aircraft and space vehicles.
Chief Editor, Professor Zhao, is based at the University of Canterbury and his research interests include applying theoretical, numerical and experimental approaches to study combustion instability, thermoacoustics and aerodynamics.
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Study of the Mechanical Properties of a CMDB Propellant Over a Wide Range of Strain Rates Using a Group Interaction Model
Composite modified double base (CMDB) propellants are heterogeneous propellants in which properties are significantly improved by adding solid particles into the polymer matrix. A molecular group interaction model that can predict the mechanical properties of polymers through a molecular structure is used to predict the viscoelastic behavior of the CMDB propellant. Considering that the addition of solid particles will improve the crosslinking degree between polymer molecules and reduce its secondary loss peak, the input parameters of the model are modified through dynamic mechanical analysis (DMA) experimental data. By introducing the strain rate into the expression of model glass transition temperature, the mechanical properties of propellant over a wide strain range ( s-1 ~ 3000 s-1) are obtained. The reliability of the model is verified by comparison with uniaxial compression test data. By modifying the input parameters of the model, the effects of different mass ratios of nitrocellulose (NC)/nitroglycerin (NG) on the mechanical properties of the CMDB propellant were analyzed. The results show that the glass transition loss increases with increasing mass ratio of NC/NG, while Young’s modulus and yield stress decrease.
Enhancing Short-Term Prediction of BDS-3 Satellite Clock Bias Based with BSO Optimized BP Neural Network
The satellite clock bias (SCB) prediction plays an important role in high-accuracy and real-time navigation and positioning. When predicting the SCB, the performance of the BP neural network is affected by the local optimum due to inaccurate initial parameters. Therefore, we propose an improved BP neural network based on the beetle swarm optimization (BSO-BP) algorithm to improve the performance of SCB prediction in third-generation Beidou satellite navigation system (BDS-3). The proposed model takes advantage of group learning strategy to optimize the initialization parameters of the BP neural network and obtains globally optimized parameters. In order to verify the proposed BSO-BP model, 15 BDS satellites are analyzed in terms of prediction accuracy and stability of SCB. The experimental results show that when predicting 1 hour SCB based on a 12 hours SCB data, the prediction accuracy of the BSO-BP model is the best, with an average accuracy of 0.064 ns. As compared with the LP, QP, and GM models, the average prediction accuracy of the proposed BSO-BP model increases by about 72.6%, 43.4%, and 86%, respectively. As the prediction time increases, the influence of the inaccurate initial parameters on SCB prediction gradually decreases, and the prediction accuracy improves. The proposed BSO-BP model has the best accuracy and stability when predicting the 1 h SCB based on the same data. The prediction stability of the proposed BSO-BP model improves by more than 36% as compared with LP, QP, and GM models. In addition, the prediction accuracies of PHM clock and Rb-II clock improved by more than 47%, as compared with that of the Rb clock. Therefore, the overall performance of the atomic clock based on BDS-3 is better than BDS-2. The positioning accuracy of the BSO-BP model can reach the centimeter level in east, north, and up directions.
Pretension Design and Analysis of Deployable Mesh Antenna considering the Effect of Gravity
The difference between the space and the earth environment has significantly influenced the shape accuracy of the antenna reflector surface. With the increasing demand for the aperture of the antenna reflector, gravity has become one of the main factors that restrict the accuracy. In this paper, a new method for pretension design considering the effect of gravity is proposed. The design surface can be well restored to the ideal surface in orbit. Meanwhile, this method can avoid flipping antenna reflectors or extensive experiments for modification during ground adjustment. Then, the feasibility and effectiveness of the design method are validated by several numerical simulations. Moreover, the results are compared with the previous method and the differences have been discussed in detail. Finally, the effects of cable radius, cable length, and elastic modulus of the mesh reflector have been researched, respectively.
Finite-Time Orbit Control for Spacecraft Formation with External Disturbances and Limited Data Communication
This work addresses the finite-time orbit control problem for spacecraft formation flying with external disturbances and limited data communication. A hysteretic quantizer is employed for data quantization in the controller-actuator channel to decrease the communication rate and prevent the chattering phenomenon caused by the logarithmic quantizer. Combined with the adding one power integrator method and backstepping technique, a new finite-time tracking control strategy with adaptation law is designed to ensure that the closed-loop system is practical finite-time stable, and that the tracking errors of relative position and velocity are bounded within finite-time despite with limited data communication and external disturbances. Finally, an example is shown to validate the effectiveness of the proposed finite-time tracking controller.
A UAV Pursuit-Evasion Strategy Based on DDPG and Imitation Learning
The UAV pursuit-evasion strategy based on Deep Deterministic Policy Gradient (DDPG) algorithm is a current research hotspot. However, this algorithm has the defect of low efficiency in sample exploration. To solve this problem, this paper uses the imitation learning (IL) to improve the DDPG exploration strategy. A kind of quasiproportional guidance control law is designed to generate effective learning samples, which are used as the data of the initial experience pool of DDPG algorithm. The UAV pursuit-evasion strategy based on DDPG and imitation learning (IL-DDPG) is proposed, and the algorithm obtains the data from the experience pool for experience playback learning, which improves the exploration efficiency of the algorithm in the initial stage of training and avoids the problem of too many useless exploration in the training process. The simulation results show that the trained pursuit-UAV can flexibly adjust the flight speed and flight attitude to pursuit the evasion-UAV quickly. It also verifies that the improved DDPG algorithm is more effective than the basic DDPG algorithm to improve the training efficiency.
Application of Gap Metric to LADRC Design in Multilinear Model of SDR
The solid ducted rocket ramjet (SDR) system faces many disturbances in the process of operation, and the linear active disturbance rejection controller (LADRC) has been widely used in engineering to solve such problems. However, the SDR also has strong nonlinearity, which brings a great challenge to the application of the LADRC in the gas flow regulation of the SDR. And the problem of fast adjustment of the “compensation factor” is one of the main difficulties in LADRC. In this paper, under the LADRC frame, the gas generator system’s closed-loop stability of the SDR was analyzed and the range of compensation factors had been calculated, and then, the “gap factor” was introduced and the “cross-iteration” method was used to quickly map out the “compensation factor” in the multilinear model controller based on the variation of the zero-point position of the system and the gap metric between adjacent set points. This greatly simplifies the parameter tuning process of the LADRC when it was applied to strongly nonlinear systems. Finally, through the comparison of simulation with adaptive PI controller and model-assisted LADRC (M-LADRC), the results have shown that the control method designed in this paper can obtain satisfactory performance and has a good engineering application prospect.