Active damping control of vibrational systems

The problem of vibration suppression in large flexible space structure (LFSS) is investigated. Based on the structure property of LFSS, an active damping strategy is proposed to effectively attenuate the critical vibrations of the structure subject to modeling uncertainty and external disturbance. Control algorithms are derived with the aim of suppressing both the vibrating magnitude and vibrating rate to an acceptable level. It is shown that the strategy exhibits robust and adaptive properties and is truly model-independent. The novelty of the proposed approach lies in the fact that it is fairly easy to set up the strategy and the overall computation involved is much less than any other strategies available to date. A two-bay truss is used to verify the validity of the proposed approach     

软件测试的控制论方法

 软件测试被认为是软件开发过程中理解最为不清的一环。部分原因是虽然有很多策略被定义和分析,但很少有策略被设计和优化。软件测试的反馈机制迄今尚未形成。基于此种情况,软件测试的控制论方法将软件测试问题当作控制问题,被测软件当作被控对象,软件测试策略当作相应的控制器,被测软件和测试策略构成一个闭环反馈控制系统。软件控制论是一门探讨软件理论和工程与控制理论和工程交叉的学科,软件测试的受控马尔可夫链方法利用受控马尔可夫链理论设计和优化软件测试策略,是软件控制论思想的体现。在受控马尔可夫链方法的框架内讨论软件系统的自适应测试,并与随机测试进行比较,发现自适应测试方法相对于传统的随机测试方法具有较大的优越性。     

混合数据及未知权值下的维修策略决策方法

采用模糊偏好规划法从模糊成对比较集中求取各属性的权值,然后应用基于随机优势和模糊数质心距的ELECTREⅢ方法来对备选维修策略进行排序,以确定最佳的维修策略.最后将其应用到航空发动机的维修策略决策中.结果表明,提出的方法能有效地解决混合数据及未知权值下的维修策略决策问题.      

基于启发式自适应离散差分进化算法的多UCAV协同干扰空战决策

 研究了多无人作战飞机(UCAV)协同干扰空战决策(MUCJAD)问题,在干扰效能评估指标量化方法的基础上为该问题建立了优化模型。为有效求解该模型,提出一种启发式自适应离散差分进化(H-SDDE)算法。在H-SDDE算法中,设计了包含4种候选解产生策略的候选策略池,引入了候选解产生策略及其参数的自适应学习过程。此外,结合实际问题为算法设计了基于威胁度的扩展型整数编码方案、基于威胁度的启发式个体调整操作、基于约束满足的个体修复操作。在12个测试实例上进行了仿真验证,结果表明,H-SDDE算法与其他同类算法相比在求解质量和求解速度上具有明显优势,能够更好地发挥多UCAV协同干扰整体效果。     

复杂退化系统的组合维修策略优化

由于现有视情维修研究中没有考虑定期维护的影响,无法准确反映定期维护下的系统性能退化规律,因而不利于合理制定定期维护与视情维修组合的维修策略。针对该问题,重点开展了该组合维修策略下的性能退化建模与维修决策研究。通过结合组合维修策略下的性能退化特点,从失效机理出发,利用复合Poisson过程建立了性能退化模型,并通过退化强度函数描述了仅恢复累积性能退化量而不改变性能退化规律的维修效果。同时,分析了该条件下的可靠度函数,说明了其具有阶梯型变化和突变性的特性。基于性能退化模型,建立了长期运行条件下以费用率最低为目标、失效风险为约束的组合维修决策优化模型,并求解确定了最优维护周期和预防性维修阈值。通过数值分析,描述了费用率随维修策略值变化的规律,说明了优化解的存在性。同时,通过与系统自身寿命规律比较,说明采用该优化模型,可以有效地延长系统的使用时间,实时控制失效概率,确保其具有较高的安全等级,进而有效地降低维修费用。     

带自调整因子的防滑刹车系统模糊控制器研究

模糊控制不需要系统精确的数学模型,具有一定的学习、推理功能,能够将人类的经验应用到系统中,非常适合飞机的防滑刹车控制系统。本文将采用模糊控制设计防滑刹车的控制策略,并应用自调整因子算法对模糊控制的参数进行优化。     

Multitarget Bayes filtering via first-order multitarget moments

The theoretically optimal approach to multisensor-multitarget detection, tracking, and identification is a suitable generalization of the recursive Bayes nonlinear filter. Even in single-target problems, this optimal filter is so computationally challenging that it must usually be approximated. Consequently, multitarget Bayes filtering will never be of practical interest without the development of drastic but principled approximation strategies. In single-target problems, the computationally fastest approximate filtering approach is the constant-gain Kalman filter. This filter propagates a first-order statistical moment - the posterior expectation - in the place of the posterior distribution. The purpose of this paper is to propose an analogous strategy for multitarget systems: propagation of a first-order statistical moment of the multitarget posterior. This moment, the probability hypothesis density (PHD), is the function whose integral in any region of state space is the expected number of targets in that region. We derive recursive Bayes filter equations for the PHD that account for multiple sensors, nonconstant probability of detection, Poisson false alarms, and appearance, spawning, and disappearance of targets. We also show that the PHD is a best-fit approximation of the multitarget posterior in an information-theoretic sense.     

Distributed formation control of multiple aerial vehicles based on guidance route

Formation control of fixed-wing aerial vehicles is an important yet rarely addressed problem because of their complex dynamics and various motion constraints, such as nonholonomic and velocity constraints. The guidance-route-based strategy has been demonstrated to be applicable to fixed-wing aircraft. However, it requires a global coordinator and there exists control lag, due to its own natures. For this reason, this paper presents a fully distributed guidance-route-based formation approach to address the aforementioned issues. First, a hop-count scheme is introduced to achieve distributed implementation, in which each aircraft chooses a neighbor with the minimum hop-count as a reference to generate its guidance route using only local information. Next, the model predictive control algorithm is employed to eliminate the control lag and achieve precise formation shape control. In addition, the stall protection and collision avoidance are also considered. Finally, three numerical simulations demonstrate that our proposed approach can implement precise formation shape control of fixed-wing aircraft in a fully distributed manner.     

基于满意博弈论的复杂低空飞行冲突解脱方法

复杂低空空域环境下多飞行器冲突解脱方法可以有效地提供冲突解脱策略,实时规划飞行器四维航迹,避免飞行器之间发生危险接近事故或者碰撞,从而保障空域运行安全。然而,随着飞行器数目的不断增长,冲突解脱面临"维数灾难",导致问题具有高维度、强耦合等难点。因此,传统的优化方案难以得到令人满意的方案。为了提高冲突解脱效率,保障运行安全,基于满意博弈论方法,考虑低空飞行器运动特点,构建冲突解脱模型,设计冲突解脱方法。飞行器主要采用改变航向角的策略。通过基于条件概率的方法来建立"社会关系",即当前飞机所做的决策对其他飞机产生的影响。每个飞行器在决策时,都会受到优先级比自己高的决策者的影响。基于满意博弈论的冲突解脱方法不仅可以有效地解决当前飞行器的冲突问题,而且兼顾探测范围内的其他飞行器,避免当前解脱策略导致与其他飞行器冲突,实现整体最优化。最后,通过在极端典型飞行冲突场景中实验验证表明,基于满意博弈论的冲突解脱方法可以实时高效实现大规模飞行器的冲突解脱,保障飞行安全且控制经济成本。     

Embryonic array configuration optimization method based on reliability and hardware consumption

Embryonic Array(EA) with different configuration methods will directly affect its reliability and hardware consumption. At present, EA configuration design is lack of quantitative analysis method. In order to reasonably optimize EA configuration design, an EA configuration optimization design method is proposed, which is based on the constraints of EA hardware consumption and reliability. Through the analysis of EA working process and composition, quantitative analysis of EA reliability and hardware consumption are completed. Based on the constraints of EA hardware consumption and reliability, the mathematical model of EA configuration optimization design is established, which transfers EA configuration optimization design into an integer nonlinear programming model problem. According to the difference of the fitness value of individual waiting for mutation in population, adaptive mutation operator and crossover operator are selected, and a novel Modified Adaptive Differential Evolution(MADE) algorithm is proposed,which is used to solve EA configuration optimization design problem. Simulation experiments and analysis indicate that the MADE is able to effectively improve the speed, accuracy and stability of algorithm. Moreover, the proposed EA configuration optimization design method can select the most reasonable EA configuration design, and play an important guiding role in EA optimization design.     

不确定环境下多无人机任务分配

针对复杂战场环境下无人机与攻击目标之间距离的不确定性,将该距离抽象为一个区间数。在此基础上,构建了不确定环境下多无人机任务分配的数学模型。根据多无人机任务分配问题的特殊性,重新设计了差分进化算法的编码方式、变异操作、交叉操作等。其中,选择操作中,在区间数排序方法的基础上,依照可能度来计算候选解被选中的概率。鉴于差分进化算法中不同变异策略的内在特点和适用场合不尽相同,提出了 3种多变异策略的差分进化算法,以便最大限度地发挥各种变异策略的技术优势。针对 CEC2013测试函数和多无人机任务分配问题分别开展仿真实验,实验结果表明,多变异策略的差分进化算法其性能改进显著,非常适合于求解多无人机任务分 配问题。     

GH4169合金矩形截面环轧制曲线的实验研究

 轧制曲线是环件轧制工艺设计的核心问题，尤其对钛合金和高温合金这类难变形材料环件，它是影响显微组织和尺寸精度的关键因素。采用不同类型的轧制曲线对相同尺寸GH4169合金矩形截面环进行了双向轧制实验研究，主要分析了轧制曲线类型对环件温度、环件径向增长速率、双向轧制力的影响。结果表明,“上凸型”轧制曲线有利于控制环件温升，“下凹型”轧制曲线则能较好地降低轧制力能和提高环件尺寸精度。另外，为了能更有效地控制环件截面角部的温升，保证截面组织均匀，提出了GH4169合金这类难变形材料矩形截面环轧制的特殊轧制曲线。     

基于线性规划的多操纵面重构控制研究

为实现多操纵面飞机的重构控制,提高飞机飞行的安全性能,提出了一种基于线性规划的多操纵面重构控制策略.针对操纵面卡死、松浮、损伤等典型故障情况,推导了相应的重构分配器,通过基于线性规划的直接分配方法来实现在操纵面故障下的重构控制.仿真结果表明,该控制策略能有效处理典型操纵面故障,发生故障时仍能快速跟踪控制指令,保证较好的...     

Evasion guidance algorithms for air-breathing hypersonic vehicles in three-player pursuit-evasion games

In practical combat scenario, the cooperative intercept strategies are often carefully designed, and it is challenging for the hypersonic vehicles to achieve successful evasion. Based on the analysis, it can be found that if several Successive Pursuers come from the Same Direction (SPSD) and flight with a proper spacing, the evasion difficulty may increase greatly. To address this problem, we focus on the evasion guidance strategy design for the Air-breathing Hypersonic Vehicles (AHVs) under the SPSD combat scenario. In order to avoid the induced influence on the scramjet, altitude and speed of the vehicle, the lateral maneuver and evasion are employed. To guarantee the remnant maneuver ability, the concept of specified miss distance is introduced and utilized to generate the guidance command for the AHV. In the framework of constrained optimal control, the analytical expression of the evasion command is derived, and the constraints of the overload can be ensured to be never violated. In fact, by analyzing the spacing of the pursers, it can be classified whether the cooperative pursuit is formed. For the coordination-unformed multiple pursers, the evasion can be achieved lightly by the proposed strategy. If the coordination is formed, the proposed method will generate a large reverse direction maneuver, and the successful evasion can be maintained as a result. The performance of the proposed algorithms is tested in numerical simulations.     

结冰飞机着陆阶段飞行安全包线确定及操纵应对策略

结冰会导致飞行安全包线收缩、严重威胁飞行安全,研究结冰后安全包线变化对于操纵应对策略设计及提高飞行安全具有重要意义。以美国国家航空航天局（NASA）的项目飞机GTM（Generic Transport Model）为研究对象,通过对飞机的气动参数进行多项式拟合,建立了结冰飞机纵向通道的动力学模型。为了得到能随结冰程度变化的安全包线,将可达性分析理论引入到对结冰飞机着陆过程的安全性分析。提出将正向可达集与反向可达集的交集作为飞行安全包线,其中可达集的确定是基于水平集方法求解哈密尔顿-雅克比方程的最优解。最后针对不同程度的结冰条件进行了操纵时域验证,并提出了相应的操纵控制策略。研究结果表明,轻度结冰对安全包线影响较小,整个着陆过程的飞行状态始终能在最优控制指导下保持在安全包线以内;但对于重度结冰,飞行安全包线收缩严重,常规操纵已经很难使飞机达到着陆要求,需要进行飞行状态改出处理。研究结果为指导飞行操纵及实时包线保护打下基础。     

Integrated active fault-tolerant control using IMM approach

An integrated fault detection, diagnosis, and reconfigurable control scheme based on interacting multiple model (IMM) approach is proposed. Fault detection and diagnosis (FDD) is carried out using an IMM estimator. An eigenstructure assignment (EA) technique is used for reconfigurable feedback control law design. To achieve steady-state tracking, reconfigurable feedforward controllers are also synthesized using input weighting approach. The developed scheme can deal with not only actuator and sensor faults, but also failures in, system components. To achieve fast and reliable fault detection, diagnosis, and controller reconfiguration, new fault diagnosis and controller reconfiguration mechanisms have been developed by a suitable combination of the information provided by the mode probabilities from the IMM algorithm and an index related to the closed-loop system performance. The proposed approach is evaluated using an aircraft example, and excellent results have been obtained     

基于Proximal-Newton-Kantorovich凸规划的空天飞行器实时轨迹优化

针对空天飞行器大气层内上升段实时轨迹优化问题，提出一种基于Proximal-Newton-Kantorovich凸规划的轨迹优化方法。首先，应用Newton-Kantorovich迭代方法将轨迹优化问题转化为一系列的子问题，每个子问题都是一个线性最优控制问题；其次，针对Newton-Kantorovich迭代方法忽略运动方程中的高阶信息，导致难以收敛这一问题，提出Proximal-Newton-Kantorovich迭代方法，在子问题的性能指标中加入邻近规则化项，改善了Newton-Kantorovich迭代方法的收敛性；最后，将子问题离散为二阶锥规划问题，并应用内点法进行求解。提出的Proximal-Newton-Kantorovich凸规划方法是一种求解非线性轨迹规划问题的可行途径。理论分析表明，Proximal-Newton-Kantorovich迭代方法的收敛结果一定是轨迹优化问题的局部最优解。数值实验表明，此方法的计算时间在毫秒级。     

Strategic flight assignment approach based on multi-objective parallel evolution algorithm with dynamic migration interval

The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategic plan to reduce the flight delay and airspace congestion by reasonably regulating the air traffic flow of China. However, it is a large-scale combinatorial optimization problem which is difficult to solve. In order to improve the quality of solutions, an effective multi-objective parallel evolution algorithm(MPEA) framework with dynamic migration interval strategy is presented in this work. Firstly, multiple evolution populations are constructed to solve the problem simultaneously to enhance the optimization capability. Then a new strategy is proposed to dynamically change the migration interval among different evolution populations to improve the efficiency of the cooperation of populations. Finally, the cooperative co-evolution(CC) algorithm combined with non-dominated sorting genetic algorithm II(NSGA-II) is introduced for each population. Empirical studies using the real air traffic data of the Chinese air route network and daily flight plans show that our method outperforms the existing approaches, multiobjective genetic algorithm(MOGA), multi-objective evolutionary algorithm based on decomposition(MOEA/D), CC-based multi-objective algorithm(CCMA) as well as other two MPEAs with different migration interval strategies.     

A strategic flight conflict avoidance approach based on a memetic algorithm

Conflict avoidance （CA） plays a crucial role in guaranteeing the airspace safety. The cur- rent approaches, mostly focusing on a short-term situation which eliminates conflicts via local adjust- ment, cannot provide a global solution. Recently, long-term conflict avoidance approaches, which are proposed to provide solutions via strategically planning traffic flow from a global view, have attracted more attentions. With consideration of the situation in China, there are thousands of flights per day and the air route network is large and complex, which makes the long-term problem to be a large-scale combinatorial optimization problem with complex constraints. To minimize the risk of premature convergence being faced by current approaches and obtain higher quality solutions, in this work, we present an effective strategic framework based on a memetic algorithm （MA）, which can markedly improve search capability via a combination of population-based global search and local improve- ments made by individuals. In addition, a specially designed local search operator and an adaptive local search frequency strategy are proposed to improve the solution quality. Furthermore, a fast genetic algorithm （GA） is presented as the global optimization method. Empirical studies using real traffic data of the Chinese air route network and daily flight plans show that our approach outper- formed the existing approaches including the GA .based approach and the cooperative coevolution based approach as well as some well-known memetic algorithm based approaches.     

深空探测器定位在共线平动点附近的线性策略

深空探测器需要定位在日-地(月)系的共线平动点L1或L2附近执行探测任务,但由于共线平动点的不稳定性,必须在运行期间进行轨控。对于条件周期轨道(如晕轨道)必须在控制过程中考虑高次项,控制条件复杂,技术上实现相对困难。而某些探测任务,探测器定位在共线平动点附近的条件拟周期轨道(对应L issajous轨道)上亦可以。这种类型的轨道可以离共线平动点较近,那么只需要在控制过程中考虑线性项即可,控制条件简单。以圆型限制性三体问题作为基本模型,采用预估-校正法逼近线性化模型下的目标轨道,给出在轨运行期间的轨控策略亦是可取的,这种控制措施相对而言较简单,容易实现。仿真计算结果表明是可行的,能够提供较高的位置精度。