最后接近段交会对接飞行器人机联合控制的仿真研究

建立了一套交会对接人、机联合控制特性仿真实验系统的方法,设定对接控制的精度要求,选用26名年龄在20～40岁的男性青年志愿者进行了最后接近段交会对接的人机联合控制实验。实验的评价指标为追踪飞行器姿控与推进发动机点火的累计时间以及对接任务的成功率。实验结果表明,当受试者完成控制不多于3个相对参数,而其余由自动控制来完成时所形成的人、机联合控制的成功率在88.24%以上。此外,经过充分训练后,也有二名受试者完成了全部相对位置和姿态参数的控制。因此,在设计两飞行器的交会对接任务时,若要考虑到航天员的参与作用,让其完成控制两航天器间的俯仰、偏航和滚转参数较为合适,并且可以节省燃料。如果让航天员承担全部的参数控制任务,这就要考虑两方面的条件,一是允许消耗足够多的燃料,二是操作时间没有限制。     

An Efficient Constrained Model Predictive Control Algorithm Based on Approximate Computation

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Scheduling algorithm based on critical tasks in heterogeneous environments

Heterogeneous computing is one effective method of high performance computing with many advantages. Task scheduling is a critical issue in heterogeneous environments as well as in homogeneous environments. A number of task scheduling algorithms for homogeneous environments have been proposed, whereas, a few for heterogeneous environments can be found in the literature. A novel task scheduling algorithm for heterogeneous environments, called the heterogeneous critical task （HCT） scheduling algorithm is presented. By means of the directed acyclic graph and the gantt graph, the HCT algorithm defines the critical task and the idle time slot. After determining the critical tasks of a given task, the HCT algorithm tentatively duplicates the critical tasks onto the processor that has the given task in the idle time slot, to reduce the start time of the given task. To compare the performance of the HCT algorithm with several recently proposed algorithms, a large set of randomly generated applications and the Gaussian elimination application are randomly generated. The experimental result has shown that the HCT algorithm outperforms the other algorithm.     

一类分布式控制系统的容错优化调度算法

在分析同步采样分布式控制系统基础上,给出了一种新的容错调度算法。该算法首先在一个周期内形成一个任务调度序列(包括基版本和副版本),然后采用启发式算法将任务分配倒各个处理器上,且同一任务的基版本和副版本分配到不同的处理器上。同一处理器上的任务按照其在调度序列中的先后次序执行。由于控制系统的性能与任务的采样周期和控制延迟有关系,因而采用以整数编码为基础遗传算法对调度序列进行优化。仿真实验表明,这种调度算法在保证实时任务容错可调度的情况下,可以极大地提高控制系统地的性能。     

面向复杂关联测控需求的冲突规避调度算法

对卫星测控资源调度问题的现状进行了分析, 根据现有场景、需求和任务建立了目标约束满足模型。在系统阐述测控资源、可见弧段、任务需求的基础上, 考虑到测控任务需求间复杂的相互关联关系, 提出了一种基于任务冲突规避的测控资源调度算法。相比其他传统方法, 该算法考虑了全局任务对资源的需求和任务间复杂的关联性, 引入了可行解接受度函数, 避免了传统启发式算法过分贪婪的缺点。实验结果表明, 该算法应用于大规模测控任务资源调度时, 能有效提高任务调度的成功率。     

Predictive control for mechanical system with backlash based on hybrid model

The mechanical system with backlash is distinguished between a “backlash mode” and a “contact mode”. The inherent switching between the two operating modes makes the system a prime example of hybrid system. For eliminating the bad effect of backlash, a piecewise affine (PWA) model of the mechanical servo system with backlash is built. The optimal control of constrained PWA system is obtained by taking advantage of model predictive control (MPC) method, and the explicit solution of MPC in a look-up table form is figured out by combining the dynamic programming and multi-parametric quadratic programming, thereby establishing an explicit hybrid model predictive controller. Furthermore, a piecewise quadratic (PWQ) function for guaranteeing the stability of closed-loop control is found by formulating the search of PWQ function as a semi-definite programming problem. In the tracking experiments, it is demonstrated that the explicit hybrid model predictive controller has a good traction control effect on the mechanical system with backlash. The error meets the demands of real system. Further, compared to the direct on-line computation, the computation burden is reduced by the explicit solution, thereby being suitable for real-time control of system with short sampling time.     

空间机械手模拟器系统设计与实验研究

空间机器人系统复杂,需要在地面进行充分的实验以验证和评估其设计方案和控制算法。为了对系统方案中各部件电气接口设计的有效性、信息传递的正确性进行检验,同时,演示验证信息管理、任务调度的实时性,以及在轨执行任务的能力,设计并研制了一套空间机械手模拟器系统。该系统由空间机械手中央控制器模拟器、关节电模拟器、手爪电模拟器、手眼相机电模拟器、图形仿真器、空间机械手动力学模块和信息调度仿真器组成,各部件之间的电气连接与星上实际系统一致。通过HLA/RTI(Run Time Infrastructure)仿真支撑环境与航天器姿轨控系统进行信息同步和交互,实现了空间机器人在轨任务的仿真。最后提出了一种空间机器人在轨协调控制方法,利用该系统进行了空间机器人协调控制圆弧实验,实验结果表明该系统设计合理、运行稳定,采用的协调控制方法可行有效。     

基于改进MPC的协同自适应巡航控制策略研究

针对环境干扰、传感器噪声和跟随时变车速稳定性较差等问题，提出一种基于KF(kalman filtering)的改进MPC(model predictive control)算法。搭建CACC(cooperative adaptive cruise control)车辆间纵向运动学模型，并建立离散状态空间方程；利用KF对状态变量降噪，同时对预测模型进行鲁棒性设计；对不同工况下CACC控制目标进行分析，分别建立目标优化函数。通过搭建Simulink与CarSim联合仿真模型进行验证，结果表明，改进MPC算法能够提高城市与市郊工况下车辆的燃油经济性与驾乘舒适性，实现公路工况下对时变车速的稳定跟随。     

变风量空调系统的模型预测控制及仿真研究

采用基于模型预测控制策略的多输入多输出(MIMO)控制器对单通道变风量空调系统的控制问题进行了研究.在分析系统工作机理和系统动力学行为的基础上,建立了内部模型的结构,采用实验确定了模型的参数.通过设定参考轨迹、输入输出约束、控制步长、预测步长及加权矩阵,解决了系统的凸二次型优化问题.通过仿真研究和对实际系统的控制,验证了系统的控制效果.     

How Task Allocation Strategy Affects Team Performance: A Computational Experiment

This paper studies how to determine task allocation schemes according to the status and requirements of various teams, to achieve optimal performance for a knowledge-intensive team (KIT), which is different from traditional task assignment. The way to allocate tasks to a team affects task processing and, in turn, influences the team itself after the task is processed. Considering the knowledge requirement of tasks as a driving force and that knowledge exchange is pivotal, we build a KIT system model based on complex adaptive system theory and agent modeling technology, design task allocation strategies (TASs) and a team performance measurement scale utilizing computational experiment, and analyze how different TASs impact the different performance indicators of KITs. The experimental results show the recommend TAS varies under different conditions, such as the knowledge levels of members, team structures, and tasks to be assigned, particularly when the requirements to the team are different. In conclusion, we put forward a new way of thinking and methodology for real task allocation problems and provide support for allocation decision makers.     

基于拍卖算法的相控阵雷达任务调度方法

灵活有效的驻留时间调度算法是实现多功能相控阵雷达(phased array radar,PAR)工作性能优化和资源合理利用的基础。通过将时间作为拍卖物品,待调度任务作为竞拍者,设计了基于拍卖算法的PAR调度方案。该算法结合PAR的任务调度原则,以任务优先级原则和时间利用原则为标准,建立了拍卖者所得利润的竞拍价值函数。以期望执行时间原则为标准,给出了竞拍者的竞标期望函数。仿真结果显示,当PAR调度任务处于饱和时,所用算法的任务调度成功率和实现价值率依然较高,能够满足任务对平均时间偏移率的较低要求,并且能够保障高优先级任务的优先调度。     

可重构计算平台上软硬件任务划分与调度算法

软硬件任务划分和任务调度是保证任务集合在可重构计算平台上高效运行的重要技术。传统上软硬件任务划分与任务调度独立进行,划分方案和调度方案不一定匹配,加速效果难以保证。提出了一种将软硬件任务划分与任务调度相结合的算法。该算法综合考虑了任务的执行时间、任务间的通信开销、任务间的依赖关系以及计算资源间的并发关系,可以同时获得给定任务集的软硬件任务划分方案和任务调度方案,加速效果良好。算法开销与传统的任务调度算法相当,时间复杂度为O(V²log₂V+PVlog₂V)实验结果表明了该算法的可行性和有效性。     

波浪干扰下的AUV纵向运动建模与模型预测控制

针对近水面航行的AUV,研究了其波浪影响下定深控制问题。基于弗劳德—克雷洛夫假设(Froude-Krylov Hypothesis),采用切片理论计算AUV近水面运动中受到的随机波浪干扰力和力矩,并以此作为扰动项建立随机波浪作用下AUV纵向运动的线性化数学模型。采用模型预测控制方法进行仿真研究,使AUV的航行深度和俯仰角达到期望值。仿真结果表明:该方法能够有效提高AUV近水面航行过程中的抗波浪干扰能力,系统具有良好的动态性能。     

操作员-UCAV交互实时Agent 个体控制及结构

提出一个用于Agent进行任务执行决策的微控算法,以解决Agent在动态环境中所做出的任务执行决策能否满足任务截止期的问题.提出了一个两层结构的实时Agent,其中本地控制层负责Agent的个体行为控制,协作计划层则令Agent能与其它Agent通信及协作.基于以上技术,实现了操作员-UCAV实时交互Agent个体控制及结构,能够适应动态的环境、自动进行任务调度和协调,并能保证任务在复杂环境下的响应时间.     

具有可变终端代价项的非线性模型预测控制

针对离散时间非线性系统的模型预测控制问题,提出了一种具有可变自调节终端代价项的模型预测控制方案.此方案通过引入自调节因子,并对其设定不同的自调节规则,使终端代价函数项具备了可变自调节性能.证明了带有可变自调节终端代价项的模型预测控制方案可保证闭环系统的性能.为自调节因子提出了若干自调节规则,并分别分析了它们的性质.用实例证明了研究结果的有效性.     

Hierarchical resource allocation for integrated modular avionics systems

Recently the integrated modular avionics (IMA) architecture which introduces the concept of resource partitioning becomes popular as an alternative to the traditional federated architecture.A novel hierarchical approach is proposed to solve the resource allocation problem for IMA systems in distributed environments.Firstly,the worst case response time of tasks with arbitrary deadlines is analyzed for the two-level scheduler.Then,the hierarchical resource allocation approach is presented in two levels.At the platform level,a task assignment algorithm based on genetic simulated annealing (GSA) is proposed to assign a set of pre-defined tasks to different processing nodes in the form of task groups,so that resources can be allocated as partitions and mapped to task groups.While yielding to all the resource constraints,the algorithm tries to find an optimal task assignment with minimized communication costs and balanced work load.At the node level,partition parameters are optimized,so that the computational resource can be allocated further.An example is shown to illustrate the hierarchal resource allocation approach and manifest the validity.Simulation results comparing the performance of the proposed GSA with that of traditional genetic algorithms are presentod in the context of task assignment in IMA systems.     

可支持多级关键度任务的实时操作系统

为设计可支持多级关键度任务的军用实时操作系统MRTOS,首先分析了现有实时操作系统的调度机制。同时为定量描述任务的关键度,使用时间窗口来描述任务在有限时间范围内的时限错过情况。基于此描述,提出了改进型的最短紧急距离优先调度算法,该算法可保证实时任务仅错过规定数量的时限,能有效支持不同关键度任务同时运行在同一计算机上,同时可在任务量瞬时过载的情况下保证关键任务优先得到执行。最后通过仿真对最短紧急距离优先调度算法进行了例证。     

多Agent系统任务分配方法综述

任务分配问题是多Agent系统（multi Agent system, MAS）中的重要研究内容之一,即解决如何将合适的任务分配给合适的Agent以实现整体执行效果最优。在分析MAS四种典型控制架构的基础上,比较了集中式与分布式控制架构下任务分配问题的特点,并对目前MAS中的多种集中式和分布式分配方法分别进行综述。最后,从理论和应用研究两方面总结和分析了MAS任务分配问题的未来发展方向。     

Two Innovative Coalition Formation Models for Dynamic Task Allocation in Disaster Rescues

This paper addresses the problem of multi-objective coalition formation for task allocation. In disaster rescue, due to the dynamics of environments, heterogeneity and complexity of tasks as well as limited available agents, it is hard for the single-objective and single (task)-to-single (agent) task allocation approaches to handle task allocation in such circumstances. To this end, two multi-objective coalition formation for task allocation models are proposed for disaster rescues in this paper. First, through coalition formation, the proposed models enable agents to cooperatively perform complex tasks that cannot be completed by single agent. In addition, through adjusting the weights of multiple task allocation objectives, the proposed models can employ the linear programming to generate more adaptive task allocation plans, which can satisfy different task allocation requirements in disaster rescue. Finally, through employing the multi-stage task allocation mechanism of the dynamic programming, the proposed models can handle the dynamics of tasks and agents in disaster environments. Experimental results indicate that the proposed models have good performance on coalition formation for task allocation in disaster environments, which can generate suitable task allocation plans according to various objectives of task allocation.     

基于DBN威胁评估的MPC无人机三维动态路径规划

模型预测控制(model predictive control, MPC)路径规划算法适用于三维动态环境下的无人机(unmanned aerial vehicle, UAV)路径规划;动态贝叶斯网络(dynamic Bayesian network, DBN)能够有效推理战场态势,对无人机进行威胁评估。针对威胁尾随无人机时的路径规划问题,构建DBN威胁评估模型,将UAV在战场环境中的威胁态势用威胁等级概率表示,与MPC路径规划算法相结合,得到基于DBN威胁评估的MPC UAV路径规划算法。通过多组仿真分析表明,在三维动态环境下,特别是威胁尾随无人机时,基于DBN威胁评估的MPC无人机路径规划算法可以得到有效的无人机路径。