大系统分散控制的非线性影响

 在大系统的控制问题中,除了递阶控制外,分散控制是另一种重要的控制方案。局部分散镇定近来受到重视。对各子系统的局部线性反馈,由于能源限制及其他因素,常引出非线性反馈。本文将研究这样的非线性对大系统稳定性的影响。     

基于模式重要度的航空电源系统可靠性估计

针对航空电源系统可靠性分析的需要,研究现有典型系统的结构特点,提出基于模式重要度的系统可靠性估计方法。该方法首先根据航空电源各子系统的组成,采用蒙特卡罗方法对各子系统可靠性进行分析。根据子系统中各部件的模式重要度,建立子系统可靠性估计模型,进而获取并联系统和总系统的可靠性估计模型。该方法结合了蒙特卡罗方法的优势和系统本身的结构特点,既解决了复杂航空电源系统可靠性分析的难题,又克服了单纯采用蒙特卡罗方法对其进行分析时,仿真效率较低的问题。最后,采用所提出的方法对两种类型的电源系统进行仿真分析,并与单纯蒙特卡罗方法仿真分析结果进行比较,验证了该方法的可行性和有效性。     

Integrated guidance and control design of a flight vehicle with side-window detection

This paper considers the guidance and control problem of a flight vehicle with side-window detection. In order to guarantee the target remaining in the seeker's sight of view, the line of sight and the attitude of the flight vehicle should be under some constraints caused by the side-window, which leads to coupling between the guidance and the attitude dynamics model. To deal with the side-window constraints and the coupling, a novel Integrated Guidance and Control (IGC) design approach is proposed. Firstly, the relative motion equations are derived in the body-Line of Sight (LOS) coordinate system. And the guidance and control problem of the flight vehicle is formulated into an IGC problem with state constraints. Then, based on the singular perturbation method, the IGC problem is decomposed into the control design of the quasi-steady-state subsystem and the boundary-layer subsystem which can be designed separately. Finally, the receding horizon control is applied to the control design for the two subsystems. Simulation results show the effectiveness of the proposed approach.     

A reduced-order model for integrated GPS/INS

The dominant factor in determining the computation time of the Kalman filter is the dimension n of the model state vector. The number of computations per iteration is on the order of n³. Any reduction in the number of states will benefit directly in terms of increased computation time. In this paper, a high order model in integrated GPS/INS is described first, then a reduced-order model based on the high-order model, is developed. Finally, a faster tracking approach for Kalman filters is discussed. A typical aircraft trajectory is designed for a complex high-dynamic aircraft flight experiment. A Monte Carlo analysis shows that the reduced order model presented in this paper provides satisfactory accuracy for aircraft navigation     

模拟高度复杂流动的自适应网格算法

提出一种基于对等弧分布律进行扭转修正的自适应网格算法。该方法将三维网格系统分裂为３个单方向自适应网格子系统,在计算中与主控方程的求解格式相耦合,交替地使用。应用所构造的算法结合ＭａｃＣｏｒｍａｃｋ显式格式对喷流／绕流干扰流场进行了雷诺平均Ｎ－Ｓ方程模拟,给出了清晰的剪切层与激波波系结构。计算结果表明,该自适应网格算法可较大程度地提高ＭａｃＣｏｒｍａｃｋ格式的分辨率。     

Optimal sensor selection strategy for discrete-time stateestimators

A novel sensor selection strategy is introduced, which can be implemented on-line in time-varying discrete-time system. We consider a case in which several measurement subsystem are available, each of which may be used to drive a state estimation algorithm. However, due to practical implementation constraints (such as the ability of the on-board computer to process the acquired data), only one of these subsystems can actually by utilized at a measurement update. An algorithm is needed, by which the optimal measurement subsystem to be used is selected at each sensor selection epoch. The approach described is based on using the square root V-Lambda information filter as the underlying state estimation algorithm. This algorithm continuously provides its user with the spectral factors of the estimation error covariance matrix, which are used in this work as the basis for an on-line decision procedure by which the optimal measurement strategy is derived. At each sensor selection epoch, a measurement subsystem is selected, which contributes the largest amount of information along the principal state space direction associated with the largest current estimation error. A numerical example is presented, which demonstrates the performance of the new algorithm. The state estimation problem is solved for a third-order time-varying system equipped with three measurement subsystem, only one of which can be used at a measurement update. It is shown that the optimal measurement strategy algorithm enhances the estimator by substantially reducing the maximal estimation error     

基于改进姿态控制系统模型的卫星多学科优化

分析了三轴稳定卫星姿态控制分系统与其它分系统的耦合关系,选定了姿态稳定方式和姿态控制系统硬件,建立了更为精确的计算姿态控制分系统质量和功率的分析模型,然后基于多学科设计优化协同优化算法建立了总体系统、姿态控制分系统、电源分系统和结构分系统的优化模型,最后用C语言对分析模型和优化模型编程计算.结果表明,分系统模型能与总体系统模型有效协调优化,得到更好的总体性能指标.      

Robust decentralized control design for aircraft engines: A fractional type

A new decentralized control for aircraft engines is proposed. In the proposed control approach, aircraft engines are considered as uncertain large-scale systems composed of interconnected uncertain subsystems. For each subsystem, the time-varying uncertainty, including parameter disturbances and interconnections in/between subsystems, is depicted by a class of general nonlinear functions. A fractional robust decentralized control with two parts, the nominal one and the fractional one, is presented. The nominal control guarantees the asymptotical stability of the engine system without uncertainty. The fractional part aims at overcoming the influences of uncertainty. Compared to the previous studies, the presented control provides not only an extra flexibility for the system performance tuning by the fraction-type gain but also a facility for the control input calculation. The proposed control approach is applied to a turbofan engine with two subsystems. The computer simulation shows that, in the flight envelope, the fractional control not only guarantees the closed-loop system uniform boundedness and ultimate uniform boundedness but also shows good economy.     

防空导弹直接力与气动力复合控制系统设计

以大气层内拦截导弹侧向直接力和气动力的复合控制系统为研究对象，首先分析了侧向喷流与来流的干扰现象，建立了通过于扰放大因子来描述的侧喷与来流的干扰模型和侧向直接力与气动力的复合控制模型，将复合控制系统分解为直接力于系统和气动力于系统，并分别针对侧向直接力和气动力的特点设计了直接力控制于系统和气动力控制于系统，仿真分析了两个子系统的性能及复合系统的性能。     

A Novel PF-LSSVR-based Framework for Failure Prognosis of Nonlinear Systems with Time-varying Parameters

Particle filtering (PF) is being applied successfully in nonlinear and/or non-Gaussian system failure prognosis. However, for failure prediction of many complex systems whose dynamic state evolution models involve time-varying parameters, the traditional PF-based prognosis framework will probably generate serious deviations in results since it implements prediction through iterative calculation using the state models. To address the problem, this paper develops a novel integrated PF-LSSVR framework based on PF and least squares support vector regression (LSSVR) for nonlinear system failure prognosis. This approach employs LSSVR for long-term observation series prediction and applies PF-based dual estimation to collaboratively estimate the values of system states and parameters of the corresponding future time instances. Meantime, the propagation of prediction uncertainty is emphatically taken into account. Therefore, PF-LSSVR avoids over-dependency on system state models in prediction phase. With a two-sided failure definition, the probability distribution of system remaining useful life (RUL) is accessed and the corresponding methods of calculating performance evaluation metrics are put forward. The PF-LSSVR framework is applied to a three-vessel water tank system failure prognosis and it has much higher prediction accuracy and confidence level than traditional PF-based framework.     

Performance evaluation of track fusion with information matrixfilter

In a multisensor environment, each sensor detects multiple targets and creates corresponding tracks. Fusion of tracks from these, possibly dissimilar, sensors yields more accurate kinematic and attribute information regarding the target. Two methodologies have been employed for such purpose, which are: measurement fusion and state vector fusion. It is well known that the measurement fusion approach is optimal but computationally inefficient and the state vector fusion algorithms are more efficient but suboptimal, in general. This is so because the state vector estimates to be fused obtained from two sensors, are not conditionally independent in general due to the common process noise from the target being tracked. It is to be noted that there are three approaches to state vector fusion, which are: weighted covariance, information matrix, and pseudomeasurement. This research is restricted solely to performance evaluation of the information matrix form of state vector fusion. Closed-form analytical solution of steady state fused covariance has been derived as a measure of performance using this approach. Note that the results are derived under the assumptions that the two sensors are synchronized and no misassociation or merged measurement is considered in the study. Results are compared with those using Monte Carlo simulation, which was used in the past to predict fusion system performance by various authors. These results provide additional insight into the mechanism of track fusion and greatly simplify evaluation of fusion performance. In addition, availability of such a solution facilitates the trade-off studies for designing fusion systems under various operating conditions     

Integration of onboard information-control systems using the vertical coordination principle

A principle of onboard information-control system integration on the basis of the coordinating control synthesis is proposed; the synthesis provides for transfer of state variable vector in the specified set of information-computing and control subsystems into the required region in one control step.     

Decentralized reduced-order filters

Continuous and discrete methods of designing simple reduced-order local filters within a large-scale network are suggested. The filters are designed to estimate only the local variables of interest and not the entire state vector. The method has the advantage that one need not know the mathematical models of the subsystems generating the interconnection variables. The order of the filter can be small enough so that there is no computational burden associated with the filter. The disadvantage of the method is that performance is lost by using a reduced-order filter instead of a full-order filter. An example that demonstrates one application in the aerospace industry is presented     

An optimal reduced-order stochastic observer-estimator

An optimal reduced-order observer-estimator (filter) is developed which can provide a full-dimensional vector of state estimates for systems where the dimension of the measurement vector is smaller than that of the state vector and none of the measurements are noise free. The reduced-order filter consists of two subfilters each of which provides a subset of the optimal estimate. A two-step L-K transformation is employed to minimize the estimate error variance of each subfilter. The optimal reduced-order filter developed is computationally efficient     

基于非线性动态逆的SRLV再入段控制律设计

基于非线性动态逆理论,设计了亚轨道可重复使用运载器(SRLV)的再入控制律.首先,分析了SRLV再入段的数学模型,并给出了反作用推力控制系统(RCS)的控制模型;其次,将非线性动态逆方法与时标分离原则相结合,考虑飞行器姿态控制系统的外环角回路的慢变特性和内环角速度回路的快变特性,独立设计了两个回路的控制律;最后,为了增强系统的鲁棒性,分别在两个回路中引入了比例-积分反馈,有效地抑制了干扰力、力矩和非线性对消带来的逆误差.仿真结果表明,设计的控制律对SRLV再入段具有很好的控制效果.     

航空电子系统电磁环境复杂度量化评估方法

针对战场电磁环境复杂度量化评估的问题,提出一种机载航空电子系统面临电磁环境复杂度的量化评估方法。通过对构成航空电子系统的各分系统、设备工作效能的评估,实现对航空电子系统面临电磁环境复杂度的量化评估。将分系统、设备的电磁敏感度测试数据作为评估对象;将模糊数学中的多层模糊综合评判理论作为评估流程;用Dempster-Shafer 证据理论法对电磁敏感度测试中位于安全裕度曲线和敏感度曲线之间的干扰量值进行处理;将国家军用标准GJB 72A-2002《电磁干扰和电磁兼容性术语》中分系统及设备的关键性类别的规定作为权重确定的依据。在考虑无法判定工作状态区域上的数据处理中,与传统的电磁环境复杂度评估方法相比效果改善了15.7%,为解决战场电磁环境复杂性评估问题提供了一种新思路。     

Formal verification and legacy redesign

Sustaining weapons system hardware and software represents a significant and ever-increasing portion of total system cost. Hardware components are becoming obsolete much sooner while weapons system lifetimes are increasing, We must identify more cost-effective solutions to engineering and reengineering these subsystems. Verifying and validating weapons systems are two of the most costly parts of either engineering process. Traditionally, hardware validation and verification is done by simulation and testing, In the past few years, math- and logic-based formal methods tools have begun to scale up to and be applied successfully to real-world problems. Incorporating formal verification methods into engineering and reengineering processes will cost-effectively and significantly improve the level of trust and the quality of our weapons systems. Formal methods are especially well suited for redesigning current weapon systems which have become unsupportable due to component obsolescence because they help minimize the astronomical costs of rigorously reverifying the reengineered components. We believe that formal methods are an important tool for effective engineering of future weapon systems     

A new adaptive Kalman filter for navigation systems of carrier-based aircraft

The features of carrier-based aircraft’s navigation systems during the approach and landing phases are investigated. A new adaptive Kalman filter with unknown state noise statistics is proposed to improve the accuracy of the INS/GNSS integrated navigation system. The adaptive filtering algorithm aims to estimate and adapt the unknown state noise covariance Q in high dynamic conditions, when the measurement noise covariance R is assumed to be known empirically in advance. The new adaptive Kalman ...     

切换线性奇异系统能达的必要条件

在各子系统正则的条件下研究了切换线性奇异系统的能达性问题。对给定的切换序列定义了容许控制集合,以保证在该容许控制集合中的任意控制律的作用下,相应切换系统的状态都是连续的。基于切换线性奇异系统状态方程解的结构特点,定义了一系列子空间。利用所定义的子空间是循环不变子空间的特点,得到了切换线性奇异系统能达的必要条件。所给的必要条件涵盖了常规切换系统和非切换奇异系统的能达性必要条件。     

人工神经网络融合诊断航空发动机气路故障

为了提高诊断的准确性,提出了一种利用人工神经网络融合诊断航空发动机气路故障的新算法.由4个子系统有机结合起来建立了神经网络融合诊断系统,对从飞参数据中得到的气路故障数据进行预处理之后,分别输入广义回归神经网络子系统和BP神经网络子系统进行诊断,然后研究了一种新的信息融合算法对两者的诊断结果进行融合,使诊断结果的故障特征更加明显,提高了诊断的准确性.通过测试表明,该信息融合算法十分有效,具有较高的实用价值.