On-line robust trajectory generation on approach and landing for reusable launch vehicles

A major objective of next generation reusable launch vehicle (RLV) programs includes significant improvements in vehicle safety, reliability, and operational costs. In this paper, novel approaches that can deliver an RLV to its landing site safely and reliably are proposed. Trajectory generation on approach/landing (A&L) for RLVs using motion primitives (MPs) and neighboring optimal control (NOC) is first discussed. In this stage, the proposed trajectory generation approach is based on an MP scheme that consists of trims and maneuvers. From an initial point to a given touchdown point, all feasible trajectories that satisfy certain constraints are generated and saved into a trajectory database. An optimal trajectory can then be found off-line by using Dijkstra’s algorithm. If a vehicle failure occurs, perturbations are imposed on the initial states of the off-line optimal trajectory, and it is reshaped into a neighboring feasible trajectory on-line by using an NOC approach. If the perturbations are small enough, a neighboring feasible trajectory existence theorem (NFTET) is then investigated and its proof is provided as well. The approach given in the NFTET shows that a vehicle with stuck effectors can be recovered from failures in real time. However, when the perturbations become large, for example, in severe failure scenarios, the NFTET is no longer applicable and often the vehicle cannot be recovered from such failures. A new method is then used to deal with this situation. The NFTET is now extended to the trajectory robustness theorem (TRT). According to the TRT and its proof, a robustifying term is introduced to compensate for the effects of the linear approximation in the NFTET. The upper bounds with respect to input deviation are adaptively adjusted to eliminate their uncertainty. In order to obtain best performance, σ-modification is employed. The simulation results verify the excellent robust performance of this method.     

面向火箭数据分析和故障诊断的数据仓库设计

针对运载火箭测试发射数据分散存储且数据利用不充分的问题,提出了以数据仓库技术对火箭的测试发射数据进行组织和存储管理,实现对火箭数据价值的深层次发掘。根据运载火箭数据的特点,提出了数据仓库基础层、源数据层、数据交互层、数据架构层、应用层、显示层六个层次的框架设计;通过面向火箭数据分析和故障诊断的数据清洗规则设计,对不同来源、不同格式的数据进行清洗和加载;对火箭的数据应用方向进行了探索,设计了包络分析、相关性分析、故障诊断等数据分析模块。用某型号火箭测试发射数据进行了验证,结果表明,数据仓库方案切实可行,为后续火箭数据的持续性管理和分析奠定了基础。     

Injection of the maximal payload under random perturbations of parameters

Consideration was given to determination of the maximal mass of the payload that can be inserted into an elliptical orbit by the “SOYUZ-2” launch vehicle with a probability not smaller than the predefined threshold and to the case where the launch vehicle parameters and the atmospheric characteristics are described by normally distributed random variables with certain expectations and rms deviations. A procedure was proposed to estimate the payload mass, and the results of numerical modeling on the multiprocessor computer system using the real data were presented.     

战术导弹控制系统BIT设计方法

战术导弹控制系统测试是其研制、生产和交付使用阶段的重要环节,为了快速便捷地完成对控制系统功能性能指标测试,及时检测和隔离故障,保证导弹安全、准时发射,根据新一代导弹控制系统设计特点,重点针对导弹交付后使用阶段测试需求,提出一种分布式与集中式相结合的机内测试(BIT)方案,详细给出了单机分布式BIT和系统集中式BIT的设计方法,该方法在无外部设备辅助测试的条件下可覆盖控制系统所有硬件资源,实现控制系统工作状态和工作性能的快速评估,为导弹或运载火箭控制系统测试性设计提供参考。     

航天运载器舵类传动机构间隙影响研究

舵类传动机构内存在的间隙是影响航天运载器飞行稳定性、机动性和控制精确性等指标的关键因素.本文先依据影响特性将航天运载器舵类传动机构中存在的各种间隙归结为:连杆配合类间隙、摇臂配合类间隙和舵轴配合类间隙;然后基于运动学分析提出了三类间隙影响的理论分析方法,而后与多体动力学软件ADAMS的仿真结果进行对比与分析.研究表明本文所提理论分析方法可准确估计三类间隙对传动机构的影响,满足实际工程间隙超差影响分析的需求.     

A survey of multidisciplinary design optimization methods in launch vehicle design

Optimal design of launch vehicles is a complex problem which requires the use of specific techniques called Multidisciplinary Design Optimization (MDO) methods. MDO methodologies are applied in various domains and are an interesting strategy to solve such an optimization problem. This paper surveys the different MDO methods and their applications to launch vehicle design. The paper is focused on the analysis of the launch vehicle design problem and brings out the advantages and the drawbacks of the main MDO methods in this specific problem. Some characteristics such as the robustness, the calculation costs, the flexibility, the convergence speed or the implementation difficulty are considered in order to determine the methods which are the most appropriate in the launch vehicle design framework. From this analysis, several ways of improvement of the MDO methods are proposed to take into account the specificities of the launch vehicle design problem in order to improve the efficiency of the optimization process.     

基于主模型的协同设计软件架构技术研究

运载火箭总体方案论证过程中,由于涉及专业多、专业间迭代交互频繁、设计方案多变等特点,容易造成多专业协同设计时版本与技术状态的不统一,需要研究针对运载火箭产品的通用建模方法,并开发相应的软件系统;基于统一数据源的协同设计理念,结合运载火箭总体设计与数据模型特点,通过定义基础信息模型、概念模型、参数模型、外部定义模型4种数据模型,提出了针对运载火箭产品的通用主模型构建方法;将此通用建模方法软件化,搭建了基于主模型的协同设计软件系统整体架构;此架构包含主模型管理系统、主模型建模工具及应用客户端三部分,实现了多专业协同设计过程中数据与版本的统一管理、技术状态一致性分析、谱系追踪、数据展示与应用等功能;该主模型建模工具与客户端软件系统的实现,为运载火箭的总体协同设计提供了工具支撑。     

Nearly-orthogonal sampling and neural network metamodel driven conceptual design of multistage space launch vehicle

This paper presents a new design methodology for efficient conceptual design of complex systems involving multidisciplinary and computationally intensive analysis with large number of design variables. A nearly-orthogonal sampling of design space is proposed with good space filling properties to extract maximum useful information about system behavior using much lower number of trial designs. This sampled data is then used as training data for artificial neural network, which will act as a metamodel to represent the time consuming disciplinary analyses. A stage-wise interconnection of separate neural networks is also proposed for trajectory metamodel to offset dimensionality curse of neural networks. Genetic Algorithm performs global optimization by utilizing this metamodel and subsequently sequential quadratic programming performs the local optimization utilizing exact analyses. The performance of proposed methodology is investigated in this paper for the conceptual design optimization of multistage solid fueled space launch vehicle. The results show excellent approximation of highly non-linear functions using proposed sampling and drastic reduction in overall design optimization time, due to greatly reduced number of exact disciplinary analyses.     

A robust and high precision optimal explicit guidance scheme for solid motor propelled launch vehicles with thrust and drag uncertainty

A new nonlinear optimal and explicit guidance law is presented in this paper for launch vehicles propelled by solid motors. It can ensure very high terminal precision despite not having the exact knowledge of the thrust–time curve apriori. This was motivated from using it for a carrier launch vehicle in a hypersonic mission, which demands an extremely narrow terminal accuracy window for the launch vehicle for successful initiation of operation of the hypersonic vehicle. The proposed explicit guidance scheme, which computes the optimal guidance command online, ensures the required stringent final conditions with high precision at the injection point. A key feature of the proposed guidance law is an innovative extension of the recently developed model predictive static programming guidance with flexible final time. A penalty function approach is also followed to meet the input and output inequality constraints throughout the vehicle trajectory. In this paper, the guidance law has been successfully validated from nonlinear six degree-of-freedom simulation studies by designing an inner-loop autopilot as well, which enhances confidence of its usefulness significantly. In addition to excellent nominal results, the proposed guidance has been found to have good robustness for perturbed cases as well.     

Solving fuzzy capacitated location routing problem using hybrid variable neighborhood search and evolutionary local search

A fuzzy capacitated location routing problem (FCLRP) is solved by using a heuristic method that combines variable neighborhood search (VNS) and evolutionary local search (ELS). Demands of the customer and travel times between customers and depots are considered as fuzzy and deterministic variables, respectively in FCLRP. Heterogeneous and homogeneous fleet sizes are performed together to reach the least multi-objective cost in a case study. The multi-objective cost consists of transportation cost, additional cost, vehicle waiting cost and delay cost. A fuzzy chance constrained programming model is added by using credibility theory. The proposed method reaches the solution by performing four stages. In the first stage, initial solutions are obtained by using a greedy heuristic method, and then VNS heuristic, which consists of seven different neighborhood structures, is performed to improve the solution quality in the second stage. In the third stage, a perturbation procedure is applied to the improved solution using ELS algorithm, and then VNS heuristic is applied again in the last stage. The combination of VNS and ELS is called VNSxELS algorithm and applied to a case study, which has fifty-seven customers and five distributing points, effectively in a reasonable time.