虚拟作战系统的演化建模研究

提出虚拟作战系统演化模型的内涵、研究目的与目标;研究了虚拟作战系统仿真原理与建模过程以及演化建模方法,提出了基于主体的虚拟作战系统演化建模方法;设计了虚拟作战系统演化模型体系结构,总结了虚拟作战系统模型的组合层次,并给出了模型间的信息控制关系。     

无刷直流电机控制系统的建模及仿真

分析了无刷直流电机的工作原理和数学模型,建立了无刷直流电机以及双闭环控制系统的仿真模型,并对系统进行了仿真.通过分析仿真结果,验证了仿真模型的合理性.从而加快了实际控制系统的设计过程.     

机器学习辅助湍流建模在分离流预测中的应用

数据驱动湍流建模是近年来发展的提高雷诺平均N-S方程预测精度的有效手段,通过机器学习算法能够从高置信度数据中自动提取特征,建立准确的从平均流动特征到雷诺应力的预测模型。针对高雷诺数下积冰翼型绕流这一类典型的复杂流动分离问题,基于此前研究者提出的机器学习预测框架,从输入输出特征选择和翼型绕流中数据分布特性两个方面出发,对机器学习预测结果的光滑性和准确性进行改善。提出了基于雷诺应力张量分析和流动特征辨识的输入特征选择准则;提出了局部区域建模方法以及基准模型和机器学习预测模型混合的代入计算方法。将改进方法应用于积冰翼型绕流问题之中,结果表明改进的方法能够准确给出训练集和预测集上的雷诺应力结果,并且代入平均流计算可以得到和真实分布更加接近的流动和机翼表面压力分布。     

空天飞行器制导控制技术研究进展与展望

本文在简要介绍空天飞行器制导控制技术发展情况基础上,针对其典型的任务形态给制导控制技术带来的挑战,分别从动力学建模、轨迹优化与制导、飞行控制与导航等四个方面阐述了制导控制技术中面临的关键技术,并探讨了空天飞行器制导控制技术后续发展方向与思路。     

Dynamics modeling and pressure control of composites tape winding system based on LQSMC

Pressure fluctuations during the composite fiber winding process seriously affect the product's compactness strength, fatigue resistance, stress uniformity, and resin content. The accuracy of pressure control systems is affected by nonlinear disturbances, such as friction, parameter perturbation, and measurement noise. A robust control algorithm based on linear quadratic optimal control and sliding mode control (LQSMC) is proposed to overcome these problems. The method is based on the system state space expression and linear quadratic optimal control. The state space model of the system is improved by using a Kalman filter and control input for state estimation, and a new sliding surface equation is defined. The ameliorated control algorithm exhibits good performance and can effectively suppress sliding mode control (SMC) chattering. Simulation and experimental results show that LQSMC offers high control precision, much stronger anti-interference, and robustness, which can effectively improve the positioning and tracking accuracy of a pressure control system compared with linear quadratic optimal control (LQC). The winding pressure control precision is improved by 45% to 50%. The results show that the porosity of composite fiber tape winding products decreased thanks to our method.     

Modeling satellite battery aging for an operational satellite simulator

During the satellite’s operations, simulation tools perform an important role in ensuring the space mission success. In this sense, the models implemented in the context of an operational satellite simulator that enables analysis of health status and maintenance during operations shall reflect the current satellite behavior with high fidelity. Moreover, it is complicated to obtain all analytical models of a satellite’s disciplines, considering its aging. This paper proposes an Artificial Neural Network (ANN) to reproduce the battery voltage behavior of a large sun-synchronous remote sensing satellite, the CBERS-4, currently in operation. Using the genetic algorithm to find the best network architecture of ANN, the neural model for this application presented an error of less than 1%, demonstrating its feasibility to obtain a high fidelity model for an operational simulator enabling extend analyses. The paper addresses advanced techniques aligned with the space industry’s future, increasing the ability to analyze a large amount of data and improve the space system’s operation.     

基于飞行参数的舰载机拦阻力统计建模与预计

拦阻钩是舰载飞机最重要的特征部件之一，对其受载进行测量、统计建模与预计具有重要的工程意义。在飞机拦阻动力学分析基础上确定了飞行数据统计建模所需的关键参数，结合某型机载荷试飞、机舰适配性试验，实测研究了飞机拦阻实际受载特点，采用线性或非线性方法统计建立了最大拦阻力与常规飞行参数之间的拟合函数关系，并得到了最大拦阻力的预计模型。建模、验模与预计结果表明，所选关键参数合理，能够充分反映拦阻钩的受载及其主要影响因素，采用纵向过载、啮合速度和发动机高压转速等参数建立的拦阻载荷统计模型可用于拦阻着陆或着舰试验时最大拦阻力的有效预测。     

轨道误差对空间站高精度时间比对的影响分析及修正方法

针对空间站飞行轨道的特点，从理论上分析了空间站轨道误差对单向和共视时间比对的影响，并通过仿真试验对理论分析结果进行校验，研究结果表明轨道误差对空间站时间比对的影响在几百皮秒量级，是影响空间站时间比对精度的主要误差源。提出一种适用于两个地面站间进行高精度时间比对的空间站轨道误差修正方法，通过仿真试验校验了该方法的有效性。试验结果表明，该方法能有效修正空间站轨道误差，实现精度在几十皮秒量级的两地面站间的超高精度时间比对，比对基线可达上千千米。     

Dual-frequency carrier smoothed code filtering with dynamical ionospheric delay modeling

In GNSS applications, carrier-smoothed-code is a widely used technique to combine code pseudo-range and carrier phase measurements. A dynamical ionospheric delay modeling method is proposed based on Kalman filter and least-squares theory. The level of the process noise is adaptively tuned along with the real-time KF state estimation, based on the online variance component estimation method. Meanwhile, the correlations of the time differenced carrier phase measurements are considered. This approach avoids overly optimistically evaluating the estimate and improves the transient accuracy of the estimates. A real GPS dataset is employed to check the performance of the proposed method under different conditions. The results show that the new algorithm can model the ionospheric delay variation well with different sampling intervals or even in ionospheric abnormal environment. The positioning accuracy can be confirmed, about 21%, 35% and 16% better are obtained in the N, E, and U direction than raw dataset.