Spacecraft Application of Expert Systems

Artificial Intelligence (AI) will play a major role in future spacecraft operation. Because the technology has not matured, knowledge-based systems will be incorporated in an evolutionary manner, with increasing responsibility as their performance is proven. Internal research at Boeing Aerospace Company has demonstrated that AI software development techniques, knowledge-based systems in particular, can be used to provide limited spacecraft subsystem automation. This capability represents a first step toward an evolutionary path to spacecraft automation. A likely progression will proceed to integrated subsystem control, automated planning and scheduling, plan execution, anomoly handling, and eventually to autonomous spacecraft operation. Although this paper is written in the context of Space Station the ideas and techniques identified should be easily transferable to spacecraft automation in general.     

一种基于实时性考虑的对称多处理机任务调度策略的设计

针对机载设备强实时性的特点,设计了一种对称多处理机任务调度策略.重点需要解决的问题是:就绪队列的设计和任务的分配.同时考虑多机带来的任务绑定,cache有效利用等问题.为了实现良好的系统性能,采取多种技巧提高系统的实时性,利用线程代替进程提高程序的并行度,运用代码的可重入性实现内核数据的完整性.     

Task allocation and reallocation for fault tolerance inmulticomputer systems

The goal of task allocation in a set of interconnected processors (computers) is to maximize the efficient use of resources and thus reduce the job turnaround time. Proposed is a simple yet effective method to allocate the tasks in multicomputer systems for minimizing the interprocessor communication cost subject to resource limitations defined by the system and designer. The limitations can be viewed as results from the load balancing since the execution time of each task, the number of available processors, processor speed, and memory capacity are known to the system or designer. As the number of processors increases, the probability of a failure existing somewhere in the systems at any time also increases. Very few established task allocation models have considered the reliability property. In multicomputer systems, we define system reliability as the probability that the system can run the tasks successfully. After the (nonredundant) task scheduling strategy is defined, tasks are then reallocated to processors statically and redundantly. This is a form of time redundancy, in which if some processors fail during the execution, all tasks can be completed on the remaining processors (but at a longer time). Due to static preallocation of tasks this method is simpler and thus more practical than well-known dynamic reconfiguration and rollback recovery techniques in multicomputer systems. We demonstrate the effectiveness of the task allocation and reallocation for hardware fault tolerance by illustrations of applying the methods to different examples and practical communications network multiprocessor system     

一种基于混合规则的作业车间计划调度方法

针对多品种小批量生产车间计划调度存在的复杂度高、实用性差等问题,在分析车间计划调度相关的任务、资源和约束等要素的基础上,提出了一种基于混合规则的计划调度编制算法,该算法综合考虑了零件差异性、工艺差异性、设备差异性、以及交货期约束等因素,使得该方法具有可行性高、实用性强等特点,较好地满足了离散制造车间的实际需求.     

Optimal scheduling of parallel tasks of tracking problem ontomultiprocessors

The optimal scheduling of the tasks of a multitarget tracking problem onto multiprocessors to minimize the schedule length is considered. The main impediments of the recent A* algorithm for optimal scheduling of the tasks of this problem, the space and time requirements, are reduced using three new techniques, viz. processor isomorphism, duplicated node deletion, and lower bound on completion time. The effectiveness of these techniques is analyzed and demonstrated with the above real-time critical problem     

自适应控制在飞机控制中的应用

 1979年,在自适应控制的应用研讨会上,Stein~[1],Kreisselmeier~[2]和Rynaski~[3]等分别发表了有关自适应控制在飞机控制中应用的文章。本文将通过对这些论文的综述,对自适应飞机控制的应用现状,所面临的问题,可能的应用方向和前景,建立一个较明确的认识。     

A satellite schedulability prediction algorithm for EO SPS

With notably few exceptions, the existing satellite mission operations cannot provide the ability of schedulability prediction, including the latest satellite planning service (SPS) standard-Sensor Planning Service Interface Standard 2.0 Earth Observation Satellite Tasking Extension (EO SPS) approved by Open Geospatial Consortium (OGC). The requestor can do nothing but waiting for the results of time consuming batch scheduling. It is often too late to adjust the request when receiving scheduling failures. A supervised learning algorithm based on robust decision tree and bagging support vector machine (Bagging SVM) is proposed to solve the problem above. The Bagging SVM is applied to improve the accuracy of classification and robust decision tree is utilized to reduce the error mean and error variation. The simulations and analysis show that a prediction action can be accomplished in near real-time with high accuracy. This means the decision makers can maximize the probability of successful scheduling through changing request parameters or take action to accommodate the scheduling failures in time.     

Equal allocation scheduling for data intensive applications

A new analytical model for equal allocation of divisible computation and communication load is developed. Equal allocation of load is attractive in multiple processor systems when real time information on processor and link capacity that is necessary for optimal scheduling is not available. The model includes a detailed accounting of solution reporting time. Equal allocation scheduling is compared with sequential scheduling and a new type of multi-installment scheduling. Aerospace applications include the processing of satellite imagery, radar, and sensor networks.     

航空电子系统混合实时任务的双层调度

针对航空电子系统的实时性需求,提出满足综合模块化航空电子(IMA)构架的双层任务调度算法.通过加权轮转调度激活分区,并为分区提供固定的时间窗口,增强了系统的可预测性;分区内部采用可抢占的固定优先级调度,减少了高优先级任务的响应时间.算法支持混合任务集的调度:对周期的强实时任务,建立具有任意时限的任务模型,增强了模型的通...     

基于静态优先级的调度

应用实时系统,如航空电子系统,不仅要满足调度任务的强实时约束,而且要具有较强的系统功能,即需要较高的系统任务可调度利用率。本文首先给出实时任务调度算法的分类及基于优先级调度算法的性能分析;然后详细描述了静态优先级任务系统的调度算法,以及在诸如航空电子系统数据传输网络设计中调度方案的选择。     

航空生产计划系统的模糊仿真

 飞机制造过程通常比较复杂，仿真模型可以帮助工程技术人员理解这一复杂的过程和找出系统中的瓶颈。用高级仿真技术和模糊方法于某航空企业的生产计划系统，建立模糊仿真模型和软件系统，研究生产计划的可行性，以满足生产管理的需要。     

深空探测器自主技术发展现状与趋势

深空探测器距离地球远、所处环境复杂、苛刻,利用地面测控站进行深空探测器的遥测和遥控已经很难满足探测器控制的实时性和安全性要求。深空探测器自主技术即通过在探测器上构建一个智能自主管理软件系统,自主地进行工程任务与科学任务的规划调度、命令执行、星上状态的监测与故障时的系统重构,完成无人参与情况下的探测器长时间自主安全运行,自主技术已经逐渐成为深空探测领域未来发展的一项关键技术。本文首先分析了传统测控模式对深空探测的约束,回顾了深空探测器自主技术发展的现状,分析了实现深空探测器自主运行的关键技术,包括在轨自主管理系统设计技术、自主任务规划技术、自主导航与控制技术、自主故障处理技术和自主科学任务操作技术。然后结合深空探测工程实施和技术发展需求,提出未来深空探测器自主技术发展的趋势和重点。     

深空探测器自主技术发展现状与趋势简

 深空探测器距离地球远、所处环境复杂、苛刻,利用地面测控站进行深空探测器的遥测和遥控已经很难满足探测器控制的实时性和安全性要求。深空探测器自主技术即通过在探测器上构建一个智能自主管理软件系统,自主地进行工程任务与科学任务的规划调度、命令执行、星上状态的监测与故障时的系统重构,完成无人参与情况下的探测器长时间自主安全运行,自主技术已经逐渐成为深空探测领域未来发展的一项关键技术。本文首先分析了传统测控模式对深空探测的约束,回顾了深空探测器自主技术发展的现状,分析了实现深空探测器自主运行的关键技术,包括在轨自主管理系统设计技术、自主任务规划技术、自主导航与控制技术、自主故障处理技术和自主科学任务操作技术。然后结合深空探测工程实施和技术发展需求,提出未来深空探测器自主技术发展的趋势和重点。     

Real-time expert systems for advanced power control (a statusupdate) [aerospace power system testbed]

The most recent developments in the Boeing Aerospace Autonomous Power System (APS) testbed are presented. The APS testbed is a 28-VDC system with 3-kW capability, assembled for use in developing improved control, techniques for aerospace electrical power systems. The main emphasis is on the development of a sophisticated programming environment to control concurrent execution of multiple autonomous algorithms coupled with a continuous input/output data flow. The integration of high-level control algorithms used for battery charge control into a real-time execution environment is discussed. This includes methods that allow several functions to respond to real-time input, affect/maintain expert system (shared) memory, and control the electrical power system configuration. Sophisticated schemes for scheduling these expert system control functions are required to allow real-time multitasking     

基于地面任务-空间姿态映射的敏捷卫星任务规划

面向观测时间窗口相互重叠的多点目标观测任务需求,对敏捷卫星单星单轨任务规划问题进行研究。针对传统方法在卫星机动能力受限和成像任务冗余两种情况下求解效率低的缺陷,引入任务-姿态协同规划思想。首先,建立地面任务和空间姿态映射关系,并考虑相邻任务间姿态机动时间的最优性使得卫星在观测相邻任务时无多余等待时间,以此来设计任务-姿态协同规划数学模型。其次,根据任务-姿态协同规划数学模型,设计自适应伪谱遗传算法（APGA）,用以求解满足调整时间最优性的敏捷卫星任务规划问题。最后,通过仿真实验,验证了模型和算法能够有效地解决传统算法求解敏捷卫星任务规划问题时存在的求解效率低的缺陷。     

Testing autonomous systems for deep space exploration

NASA is moving into an era of Increasing spacecraft autonomy. However, before autonomy can be routinely utilized, we must develop techniques for providing assurance that the system will perform correctly in flight. We describe why autonomous systems require advanced verification techniques, and offer some management and technical techniques for addressing the differences. Autonomous goal-driven spacecraft require advances in verification techniques because optimization (e.g., planning and scheduling) algorithms are at the core of much of autonomy. It Is the nature of such algorithms that over much of the input space an intuitively "small" change in the input results in a correspondingly "small" change in the output: This type of response typically leads one to conclude, quite reasonably, that if the two responses are correct, those responses "between" them will probably also be correct. However, there are certain regions in the input space where a "small" change in the input will result in a radically different output: One is not so inclined to conclude that all responses in these transition zones are likely to be correct. We believe, for two reasons, that these transition zones are one place where autonomous systems are likely to fail. First, boundary conditions, often a rich source of faults, are highly exercised in the transition zones, and so increase the likelihood of faults. Second, within the transition zone the algorithm outputs are likely to appear unusual, and, since the outputs of the algorithm become inputs to the remainder of the system, the whole system is probably pushed outside of its nominal usage profile: historically shown to be another good source of faults. We close with a discussion of risk management. Autonomous systems have many well-known management risk factors. Risk management and quality concerns must be pervasive, throughout all team members and the whole life-cycle of the project.     

嵌入式高可信架构中基于静态模型的调度研究

为解决嵌入式高可信软件架构中的实时调度问题,分析了现有采用分区机制的安全系统中分区调度的不足,提出了一种基于固定周期分区的静态调度模型,并采用优先级位图算法建立了两级调度机制。为了保障分区中任务的实时性和正确性,对分区中任务采用静态优先级和最早时限优先调度(EDF)动态优先级两种调度策略,分别就其任务调度条件和可调度性进行了理论研究,针对复杂的动态优先级任务提出了一种可调度条件,并通过仿真实验进一步验证了此调度条件的正确性。     

基于时钟驱动的循环调度

实时系统,诸如航空电子系统、空中交通控制系统(Air Traffic Control: ATC)等,从本质上说都是一种分布式实时系统,从理论上说,它们由三种类型的处理器组成,包括数据控制处理器、数据传输处理器和数据处理器.无论是数据控制处理器和数据处理器的数据计算任务,还是数据传输处理器的数据传输任务,它们的执行都必须满足任务的时间约束要求,从而正确完成系统设计的各项应用任务.本文将描述基于时钟驱动的循环调度策略,它不仅适用于对数据计算任务的实时调度,也适用于对数据传输任务的实时调度,最后,分析了此调度策略应用中存在的优势与劣势.     

风险驱动的安全关键实时任务调度

安全关键系统面临着日趋严峻的安全威胁,如何降低安全关键实时应用的风险成为挑战。通过结合风险评估与实时调度,给出一种风险驱动的任务调度方案。在分析非周期实时任务可调度性的基础上,提出一种基于处理器瞬态利用率、系统安全风险最小的在线调度近似算法。在不违背关键任务的时间约束和安全约束的前提下,该算法能够在低时间复杂度内得到安全性能确保的次优解。实验结果显示所提算法能明显降低安全关键实时应用的风险。具体来讲,最大安全风险可降低22.2%,并且在安全风险近似率上界为110%情况下,真实近似率最小为102.4%。     

基于能量最优的敏捷遥感卫星在轨任务规划

针对敏捷遥感卫星对多个离散观测点在轨自主任务规划问题,在考虑姿态运动方程耦合性的基础上,将问题分解为空间资源调度问题和连续最优控制问题,进而提出了一种结合伪谱法和遗传算法的混合求解算法。该算法针对基于行商问题(TSP)模型建立的空间资源调度问题模型,选用二维编码结构对观测顺序和相对观测时间进行实数编码,并采用遗传算法求解观测序列和观测时间;针对判断观测时间可行性时涉及的时间最优控制问题、以及姿态转移过程中涉及的最小能量消耗问题,将其归结为连续最优控制问题,并基于Gauss伪谱协态变量映射定理,采用Gauss伪谱法进行求解。通过与基于单纯遗传算法的规划算法进行对比试验,本文所提出的基于伪谱法和遗传算法的混合求解策略针对目标问题,在典型工况下姿态转移过程中能量消耗降低60%。