Adaptive sliding mode control of modular self-reconfigurable spacecraft with time-delay estimation

The reconstruction control of modular self-reconfigurable spacecraft (MSRS) is addressed using an adaptive sliding mode control (ASMC) scheme based on time-delay estimation (TDE) technology. In contrast to the ground, the base of the MSRS is floating when assembled in orbit, resulting in a strong dynamic coupling effect. A TED-based ASMC technique with exponential reaching law is designed to achieve high-precision coordinated control between the spacecraft base and the robotic arm. TDE technology is used by the controller to compensate for coupling terms and uncertainties, while ASMC can augment and improve TDE’s robustness. To suppress TDE errors and eliminate chattering, a new adaptive law is created to modify gain parameters online, ensuring quick dynamic response and high tracking accuracy. The Lyapunov approach shows that the tracking errors are uniformly ultimately bounded (UUB). Finally, the on-orbit assembly process of MSRS is simulated to validate the efficacy of the proposed control scheme. The simulation results show that the proposed control method can accurately complete the target module’s on-orbit assembly, with minimal perturbations to the spacecraft’s attitude. Meanwhile, it has a high level of robustness and can effectively eliminate chattering.     

异步电机模型参考自适应滑模矢量控制系统研究

在异步电机矢量控制系统中,针对温度变化所引起的定子阻值改变对系统性能的影响,利用模型参考自适应控制（Model Reference Adaptive Control,MRAC）技术对转子磁链进行了观测,并且设计了一种滑模速度调节器代替PI调节器,构建了基于模型参考自适应系统（Model Reference Adaptive System,MRAS）和滑模速度调节器的异步电机矢量控制系统。仿真结果表明：该系统能够实现磁链的准确快速辨识,具有响应速度快、鲁棒性强等优点,适用于温度变化较大的场合,为军用车辆电驱动系统的发展提供了有效的研究方法。     

Adaptive subspace detection based on two-step dimension reduction in the underwater waveguide

In the underwater waveguide, the conventional adaptive subspace detector (ASD), derived by using the generalized likelihood ratio test (GLRT) theory, suffers from a significant degradation in detection per-formance when the samplings of training data are deficient. This paper proposes a dimension-reduced approach to alleviate this problem. The dimension reduction includes two steps: firstly, the full array is divided into several subarrays; secondly, the test data and the training data at each subarray are transformed into the modal domain from the hydrophone domain. Then the modal-domain test data and training data at each subarray are processed to formulate the subarray statistic by using the GLRT theory. The final test statistic of the dimension-reduced ASD (DR-ASD) is obtained by summing all the subarray statistics. After the dimension reduction, the unknown parameters can be estimated more accurately so the DR-ASD achieves a better detection performance than the ASD. In order to achieve the optimal detection performance, the processing gain of the DR-ASD is deduced to choose a proper number of subarrays. Simulation experiments verify the improved detection performance of the DR-ASD compared with the ASD.     

Interception probability simulation and analysis of salvo of two electromagnetic coil launched anti-torpedo torpedoes

Electromagnetic coil launch is an important branch of electromagnetic launch (EML) technology, which is suitable for launching anti-torpedo torpedo (ATT). This paper focuses on the EML parameters and the interception probability of the EML two ATTs salvo. Based on the launching model of a multi-stage coil launcher, the trajectory model of the ATT and the attacking torpedo, a calculation method for the EML two ATTs salvo parameters is proposed, with the conditions of capture and interception given reasonably. An adaptive particle swarm optimization (APSO) algorithm is proposed to calculate the optimal launching parameters, by designing the adaptive inertia weight and time-varying study factors. According to the analysis of the simulation with Monte Carlo method, EML will improve the interception probability effectively, and the interception probability is affected by the launching range. The results demonstrate good performance of the proposed APSO in calculating EML parameters for the two ATTs salvo in certain combat situation. Implications of these results are particular regarding the command and decision in the anti-torpedo combat.     

自适应数据融合算法

以防空导弹指控系统作战单位为背景,通过对现有经典算法及工程化算法的分析,结合专家经验,提出了基于算法间联系的工程化自适应数据融合算法.对自适应算法的思想、规则集、算法库、推理组成和算法的实现作了详细的描述.     

BDS导航信号抗电离层闪烁载波跟踪的自适应卡尔曼滤波算法

电离层闪烁会引起导航信号幅度和相位的快速衰落,严重影响跟踪环路的精度和稳健性,而相比频率跟踪和伪码跟踪,载波跟踪环路更易受电离层闪烁的影响而失锁。因此,提出一种基于相位锁定指示自适应扩展卡尔曼滤波的北斗导航信号抗电离层闪烁载波跟踪算法,其以同相与正交支路的积分结果估计相位锁定指示值,并采用该指示作为控制参数对不同闪烁场景下扩展卡尔曼滤波的观测向量进行自适应调整,这不仅能够提高跟踪环路的精度和稳健性,而且能够降低扩展卡尔曼滤波发散的概率。实验结果验证了相关分析和所提跟踪算法的有效性。     

Research on monopulse forward-looking high-resolution imaging algorithm based on adaptive iteration

In this paper, we proposed a monopulse forward-looking high-resolution imaging algorithm based on adaptive iteration for missile-borne detector. Through iteration, the proposed algorithm automatically selects the echo signal of isolated strong-scattering points from the receiving echo signal data to accurately estimate the actual optimal monopulse response curve (MRC) of the same distance range, and we applied optimal MRC to realize the azimuth self-focusing in the process of imaging. We use real-time echo data to perform error correction for obtaining the optimal MRC, and the azimuth angulation accuracy may reach the optimum at a certain distance dimension. We experimentally demonstrate the validity, reliability and high performance of the proposed algorithm. The azimuth angulation accuracy may reach up to ten times of the detection beam-width. The simulation experiments have verified the feasibility of this strategy, with the average height measurement error being 7.8%. In the out-field unmanned aerial vehicle (UAV) tests, the height measurement error is less than 2.5 m, and the whole response time can satisfy the requirements of a missile-borne detector.     

机器人的自校正控制

本文从统一的角度给出了四种机器人的自校正控制方案,并通过仿真研究和算法的在线计算量估计,就控制性能和易实现性两个方面对各方案进行了比较。     

机械手的显式递推牛顿-欧拉动力学及其分散自适应控制的并行方案

文中推导了PUMA 560机械手的显式递推牛顿-欧拉动力学方程,提出了分散自适应控制的并行实现方案。算法复杂性分析显示了该实现方案的高效性。     

基于ANFIS的空袭目标攻击意图量化方法

为准确评估空袭目标的威胁程度和提高指挥员的防空决策水平,采用自适应神经模糊推理系统(ANFIS)对空袭目标的攻击意图量化分析。该方法将模糊推理和人工神经网络有机地结合起来,充分利用专家知识,综合集成了航向角攻击意图系数和高度攻击意图系数。仿真结果表明,建立的攻击意图量化系统反映了影响因素和攻击意图的映射规律,方法合理有效,能够为防空作战提供决策支持。