军用小涵道比涡扇发动机最大状态控制计划鲁棒性分析

军用小涵道比涡扇发动机在部件性能退化情况下推力保持稳定可有效保证战斗机的作战性能,合理的控制计划有助于实现这一目标.本文进行推力计算公式推导,从理论上分析对比了在部件性能退化情况下,几种经典最大状态控制计划发动机推力性能的变化.理论分析表明,相较于被控量为高压转子转速和涡轮落压比(或低压转子转速)的最大状态控制计划,控...     

基于Viterbi算法的扩频码与信息序列联合估计

针对短码DSSS（Direct Sequence Spread Spectrum,直接序列扩频）信号扩频码MLE（Maximum Likelihood Estimation,最大似然估计）问题,提出了一种基于Viterbi算法的扩频码搜索方法,并将其应用到同步CDMA（Code Division Multiple Access,码分多址）信号的扩频码估计中.该算法利用了扩频码码元为±1的先验知识,以向量的2-范数平方或1-范数作为度量值;每次判决扩频码码元时,计算2条可能路径的度量值,并选择使度量值最大的那条路径作为幸存路径,最终的幸存路径即为估计的扩频码;所提算法不仅计算复杂度低,而且能同时估计扩频信号的扩频码和信息序列.仿真实验表明,本算法在低信噪比时同样具有较好的性能.     

Oblique shock train motion based on schlieren image processing

In this paper, shock train motion in a Mach number 2.7 duct is studied experimentally, and large numbers of schlieren images are obtained by a high-speed camera. An image processing method based on Maximum Correlation Detection (MCD) is proposed to detect shock train motion from the schlieren images, based on which the key structures, e.g., separation positions and separation shock angles on the top and bottom walls, can be analysed in detail. The oscillations of the shock train are generated by rhombus and ellipse shafts at various excitation frequencies. According to the analysis of MCD results, the distributions of the frequency components of shock train oscillation generated by the two shafts are distinctly different, in which the motion generated by the ellipse shaft is much smoother; shock train motion is mainly characterized by the oscillation of separation position while the separation shock strength is not so sensitive to downstream disturbance; there is a hysteresis loop relation between the downstream pressure and separation position.     

Topology optimization of turbine disk considering maximum stress prediction and constraints

For the stress-constrained topology optimization of a turbine disk under centrifugal loads, the jagged boundaries of the mesh and the gray densities on the solid/void interfaces could make the calculated stress field inconsistent with the actual value. It may result in overestimating the maximum stress and thus affect the effectiveness of stress constraints. This paper proposes a new method for predicting the maximum stress to overcome the difficulty. In the process, a predicted density is newly defined to obtain stable boundaries with thin layers of gray elements, a transition factor is innovatively proposed to evaluate the effects of intermediate-density elements, two different stiffness penalty schemes are flexibly used to calculate the elastic modulus of elements, and a linear stress penalty is further adopted to relax the stress field of the structure. The proposed approach for predicting the maximum stress value is verified by the analysis of a structure with smooth boundaries and the topology optimization of a turbine disk. An updating scheme of the stress constraint in the topology optimization is also developed using the predicted maximum stress. Some key ingredients affecting the optimization results are discussed in detail. The results prove the effectiveness and efficacy of the proposed maximum stress prediction and developed stress constraint methods.     

Improving multi-target cooperative tracking guidance for UAV swarms using multi-agent reinforcement learning

Multi-Target Tracking Guidance(MTTG) in unknown environments has great potential values in applications for Unmanned Aerial Vehicle(UAV) swarms. Although Multi-Agent Deep Reinforcement Learning(MADRL) is a promising technique for learning cooperation, most of the existing methods cannot scale well to decentralized UAV swarms due to their computational complexity or global information requirement. This paper proposes a decentralized MADRL method using the maximum reciprocal reward to learn cooper...     

SINS/GNSS integrated navigation system based on maximum versoria filter

In the missile-borne Strapdown Inertial Navigation System/Global Navigation Satellite System (SINS/GNSS) integrated navigation system, due to the factors such as the high dynamics, the signal blocking by obstacles, the signal intefereces, etc., there always exist pulse interferences or measurement information interruptions in the satellite receiver, which make nonstationary measurement process. The traditional Kalman Filter (KF) can tackle the state estimation problem under Gaussian white noise, but its performance will be significantly reduced under non-Gaussian noises. In order to deal with the non-Gaussian conditions in the actual missile-borne SINS/GNSS integrated navigation systems, a Maximum Versoria Criterion Extended Kalman Filter (MVC-EKF) algorithm is proposed based on the MVC and the idea of M-estimation, which assigns a smaller weight to the anomalous measurements so as to suppress the influence of anomalous measurements on the state estimation while maintaining a relatively low calculation cost. Finally, the integrated navigation simulation experiments prove the effectiveness and robustness of the proposed algorithm.