Geometrical entropy approach for variable structure multiple-model estimation

The variable structure multiple-model(VSMM) estimation approach, one of the multiple-model(MM) estimation approaches, is popular in handling state estimation problems with mode uncertainties.In the VSMM algorithms, the model sequence set adaptation(MSA) plays a key role.The MSA methods are challenged in both theory and practice for the target modes and the real observation error distributions are usually uncertain in practice.In this paper, a geometrical entropy(GE) measure is proposed so that the MSA is achieved on the minimum geometrical entropy(MGE) principle.Consequently, the minimum geometrical entropy multiple-model(MGEMM) framework is proposed, and two suboptimal algorithms, the particle filter k-means minimum geometrical entropy multiple-model algorithm(PF-KMGEMM) as well as the particle filter adaptive minimum geometrical entropy multiple-model algorithm(PF-AMGEMM), are established for practical applications.The proposed algorithms are tested in three groups of maneuvering target tracking scenarios with mode and observation error distribution uncertainties.Numerical simulations have demonstrated that compared to several existing algorithms, the MGE-based algorithms can achieve more robust and accurate estimation results when the real observation error is inconsistent with a priori.     

Survey of maneuvering target tracking. Part V. Multiple-model methods

This is the fifth part of a series of papers that provide a comprehensive survey of techniques for tracking maneuvering targets without addressing the so-called measurement-origin uncertainty. Part I and Part II deal with target motion models. Part III covers measurement models and associated techniques. Part IV is concerned with tracking techniques that are based on decisions regarding target maneuvers. This part surveys the multiple-model methods $the use of multiple models (and filters) simultaneously - which is the prevailing approach to maneuvering target tracking in recent years. The survey is presented in a structured way, centered around three generations of algorithms: autonomous, cooperating, and variable structure. It emphasizes the underpinning of each algorithm and covers various issues in algorithm design, application, and performance.     

Ground target tracking with variable structure IMM estimator

In this paper we present the design of a Variable Structure Interacting Multiple Model (VS-IMM) estimator for tracking groups of ground targets on constrained paths using Moving Target Indicator (MTI) reports obtained from an airborne sensor. The targets are moving along a highway, with varying obscuration due to changing terrain conditions. In addition, the roads can branch, merge or cross-the scenario represents target convoys along a realistic road network with junctions, changing terrains, etc. Some of the targets may also move in an open field. This constrained motion estimation problem is handled using an IMM estimator with varying mode sets depending on the topography, The number of models in the IMM estimator, their types and their parameters are modified adaptively, in real-time, based on the estimated position of the target and the corresponding road/visibility conditions. This topography-based variable structure mechanism eliminates the need for carrying all the possible models throughout the entire tracking period as in the standard IMM estimator, significantly improving performance and reducing computational load. Data association is handled using an assignment algorithm. The estimator is designed to handle a very large number of ground targets simultaneously. A simulated scenario consisting of over one hundred targets is used to illustrate the selection of design parameters and the operation of the tracker. Performance measures are presented to contrast the benefits of the VS-IMM estimator over the Kalman filter and the standard IMM estimator, The VS-IMM estimator is then combined with multidimensional assignment to gain “time-depth.” The additional benefit of using higher dimensional assignment algorithms for data association is also evaluated     

Design for aircraft engine multi-objective controllers with switching characteristics

The aircraft engine multi-loop control system is described and the switching control theory is introduced to solve the regulating and protecting control problems in this paper. The aircraft engine multi-loop control system is firstly described and the control problems are formulated. Secondly, the theory of the smooth switching control is devoted and a new extended scheme for the smooth switching of a switched control system is introduced. Then, for the key technologies of aero-engines switching control, a design algorithm is presented which can determine which candidate controller should be put in feedback with the plant to achieve a desired performance and the procedure to design the aircraft engine multi-loop control system is detailed. The switching performance objectives and the switching scheme are given and a family of PID controllers and compensators is designed. The simulation shows that using the switching control design method can not only improve the dynamic performance of the aircraft engine control system and reduce the switching times, but also guarantee the stability in some peculiar occasions.     

基于机械能变化的超低轨道大气密度实时估计

在强大气阻力摄动作用下,超低轨道卫星的轨道高度会迅速衰减,大气密度的在轨实时估计对超低轨道卫星的轨道和姿态控制非常重要。研究了利用机械能变化率实现超低轨道卫星大气密度的实时估计方法,基于轨道摄动理论推导了在地球引力、大气阻力和控制力作用下大气密度的估计公式。仿真结果表明,该方法可有效地估计出大气密度。     

DOA estimation and mutual coupling calibration with the SAGE algorithm

In this paper, a novel algorithm is presented for direction of arrival（DOA） estimation and array self-calibration in the presence of unknown mutual coupling. In order to highlight the relationship between the array output and mutual coupling coefficients, we present a novel model of the array output with the unknown mutual coupling coefficients. Based on this model, we use the space alternating generalized expectation-maximization（SAGE） algorithm to jointly estimate the DOA parameters and the mutual coupling coefficients. Unlike many existing counterparts, our method requires neither calibration sources nor initial calibration information. At the same time,our proposed method inherits the characteristics of good convergence and high estimation precision of the SAGE algorithm. By numerical experiments we demonstrate that our proposed method outperforms the existing method for DOA estimation and mutual coupling calibration.     

变结构控制的研究现状及展望

关于变结构控制的研究，近年来在国内外受到极大重视，变结构控制的突出优点是对系统的摄动及干扰具有完全鲁棒性。本文系统地综述了变结构控制的研究进展。并就其存在的一些问题，应用及发展趋势进行了探讨。     

Satellite lithium-ion battery remaining useful life estimation with an iterative updated RVM fused with the KF algorithm

Lithium-ion batteries have become the third-generation space batteries and are widely utilized in a series of spacecraft. Remaining Useful Life (RUL) estimation is essential to a spacecraft as the battery is a critical part and determines the lifetime and reliability. The Relevance Vector Machine (RVM) is a data-driven algorithm used to estimate a battery’s RUL due to its sparse feature and uncertainty management capability. Especially, some of the regressive cases indicate that the RVM can obtain a better short-term prediction performance rather than long-term prediction. As a nonlinear kernel learning algorithm, the coefficient matrix and relevance vectors are fixed once the RVM training is conducted. Moreover, the RVM can be simply influenced by the noise with the training data. Thus, this work proposes an iterative updated approach to improve the long-term prediction performance for a battery’s RUL prediction. Firstly, when a new estimator is output by the RVM, the Kalman filter is applied to optimize this estimator with a physical degradation model. Then, this optimized estimator is added into the training set as an on-line sample, the RVM model is re-trained, and the coefficient matrix and relevance vectors can be dynamically adjusted to make next iterative prediction. Experimental results with a commercial battery test data set and a satellite battery data set both indicate that the proposed method can achieve a better performance for RUL estimation.     

Analysis of an adaptive algorithm for unbiased multipath time delay estimation

The multipath equalization time delay estimator (METDE) provides an adaptive approach for estimating the difference in arrival times of a signal received at spatially separated sensors as well as the multipath channel characteristics. However, the parameter estimates of the METDE are biased in the presence of noise. The METDE algorithm is improved for unbiased parameter estimation via minimizing a modified cost function. Convergence behaviors and variances of the system variables of the amended method are derived. Computer simulations are included to corroborate the theoretical analysis and to evaluate the adaptive multipath delay estimation performance of the proposed algorithm.     

几种非线性特性对变结构控制系统的影响研究

变结构控制(滑模控制)具有使系统在有限时间收敛、精确跟踪、对参数不确定性和外界干扰具有不变性的特点,它在控制对象模型不精确的情况下可以维持系统的稳定并能保持良好-致的性能,而且设计方法简单.然而在实际应用中变结构控制器将经受种种非线性特性对变结构控制系统的影响,文章简单分析了饱和、死区和时间滞后几种非线性特性对变结构控制系统的影响,并给出了仿真结果.     

反舰导弹串级离散变结构姿态控制

针对大空域反舰导弹控制,在串级结构的基础上,采用直接状态法建立模型,设计带有积分器的离散变结构控制器IVSC调整控制信号,实现对系统参数摄动和外部干扰的鲁棒性.     

面向试飞员培训的多构型变稳控制律设计

针对目前IFSTA变稳机控制律模式不全,不足以全面体现飞机纵、横、航向的操纵性和稳定性的问题,根据试飞员培训的具体需求,基于IFSTA响应反馈原理重新设计了多构型变稳控制律,以满足日益增长的试飞员培训需求.结果 表明,所设计的50余种模态的变稳控制律,极大地丰富了当前变稳机控制律构型,不仅可以满足未来试飞员培训的要求,...     

一类非线性系统的反演变结构控制及应用

针对一类非线性系统 ,将其变换为易于设计变结构控制规律的规范型。利用小脑关节神经网络( CMAC)估计系统中的不确定函数 ,利用 CMAC神经网络和多面滑模技术估计出变换后系统的状态 ,最后利用变结构控制技术设计出控制器 ,特点是无需已知不确定性函数及其各阶导数的上界 ,与经典设计方法相比 ,所提出的方案允许非参数化不确定性。最后将此方法应用于空空弹控制系统的设计中 ,仿真结果表明了该方法的有效性     

基于局部应力应变场强法的薄壁缺口结构随机声疲劳寿命估算

航空发动机火焰筒结构在随机声激励下的寿命估算属于典型的多轴疲劳问题。对航空薄壁结构随机声疲劳寿命估算的峰值概率密度法和功率谱密度法进行了探讨。在应力场强法的基础上,深入研究了一种用于薄壁缺口结构随机疲劳寿命估算的有效方法——局部应力应变场强法,该方法能同时考虑缺口局部应力梯度和应变梯度对疲劳损伤的影响。以薄壁缺口结构作为研究对象,结合声疲劳问题分析的一般方法,对局部应力应变场强法在声疲劳寿命估算中的运用进行了研究。     

切换拓扑下无人机集群系统时变编队控制

针对多无人机(UAV)间通信拓扑可能发生变化的情况,研究了具有二阶积分特性的无人机集群系统的轨迹跟踪与时变编队控制问题。基于一致性方法设计了编队控制器,将编队控制问题转换成闭环系统的稳定性问题,引入了切换拓扑平均驻留时间的概念,并在此基础上利用线性矩阵不等式(LMI)方法,给出了控制器设计步骤。通过构造分段连续Lyapunov函数,证明了切换拓扑下无人机集群系统能够实现对指定轨迹的跟踪并且实现时变编队飞行。以三维空间运动的无人机集群系统为例进行了仿真验证,结果表明本文所提方法能够解决切换拓扑下无人机集群系统的轨迹跟踪与时变编队问题。     

基于LQR的纵向多自由度变稳控制律设计

飞机进场着陆过程中,速度、迎角和俯仰角速度等多参数的跟踪模拟是一个复杂的多输入输出系统,采用传统的控制方法难以获得满意的控制效果.根据系统控制要求,提出一种利用最优二次型调节器(LQR)的控制方式.首先分析跟踪模拟的结构形式,把模型跟踪问题化为最优二次型状态调节器,确定控制律的基本结构;然后对某型飞机进场着陆阶段特性利用TIFS飞机进行模型跟踪控制律的设计,并结合经典控制理论对系统控制参数进行修正;最后利用舵机在回路的半物理试验台进行仿真.结果表明,所提出的LQR控制方法能够有效地解决多控制回路性能的自动协调,具有良好的动态响应,而且有很高的模型跟踪模拟精度.     

Understanding commutations in switching converters. II. Analysis and synthesis of DC-DC regulators

For pt.I see ibid., vol.39, no.1, p. 282-297 (2003). This paper illustrates a general method to formulate the equations for the analysis of commutations and of the effects caused by large step-wise perturbations, large change of parameters, and circuit failures in switching converters including transformers, feedback circuitry, and soft-switching cells. The matrix equations obtained by means of the modified nodal analysis-based method proposed in this work are useful for theoretical inspection of switching converters as well as for numerical simulations. The examples of applications concern the analysis and the synthesis of switching converters and show that the Compensation Theorem (CT)-based model may help in selecting circuit topologies valid for the circuit design.     

Understanding commutations in switching converters. I. Basic theory and application of the Compensation Theorem

The analysis of synchronous commutations in switching converters is discussed. A reduced resistive circuit for the analysis of synchronous commutations is introduced by applying the Compensation Theorem. Based on a matrix model, a new method for the analysis of both hard and soft synchronous commutations is formulated, which permits a straightforward understanding operation of switching converters. The method of analysis is presented herein in its basic version, for the analysis of nonisolated hard-switching converters, while the general formulation and its applications to the analysis and synthesis of DC-DC regulators is presented in the companion paper Part II.     

Accuracy of angle estimation with monopulse processing using twobeams

Expressions are provided for the accuracy of monopulse angle estimation using two beams. It is shown that, if the signal angle is halfway between the angles of the beams, the Cramer-Rao lower bound (CRLB) for monopulse processing is almost as small as the CRLB obtained if the entire array of sensors is used. The monopulse CRLB is considerably poorer if the angle of the signal is equal to that of one of the two beams. The expressions in this correspondence are for a uniformly weighted linear array of M equally spaced sensors, for which N⩾M beams are formed     

Attitude determination with UD implementation of decoupled bias estimation

The application of the UD implementation decoupled bias estimation to attitude determination is analyzed here. The advantage of decoupled bias estimation in general is the reduction in the dimensions of the filter and the subsequent reduction in the amount of processing. The purpose of the UD implementation is to mitigate the effects of round-off errors. A unique advantage of the application of decoupled bias estimation to attitude determination is that the bias processing can easily be turned off whenever a reconfiguration to a bias-free estimator mode is necessary. A comparison of the attitude error of the UD decoupled Kalman filter attitude uncertainty is given with respect to the coupled Kalman filter attitude uncertainty during the time periods when the bias processing is turned off. A detailed discussion of the UD implementation is given.