离散时间部分状态反馈模型参考自适应控制

本文针对线性不确定性系统, 给出了部分状态反馈直接模型参考自适应控制设计方案以及详细的系统稳 定性、输出跟踪性能分析. 控制器设计基于降维观测器和参数化方法. 此方案采用反馈控制, 反馈信号不仅仅依赖 全状态信息或者输出信号, 而是任意不超过系统维数的可测信号. 因此, 部分状态反馈控制是包含状态反馈、输出 反馈控制的新的控制方案, 缓解了状态反馈对状态信息的限制, 降低了输出反馈控制结构的复杂性. 通过引入辅助 信号, 本文证明了输出匹配条件的存在性、所有闭环系统信号的有界性以及渐近输出跟踪性能. 仿真结果验证了该 方案的有效性.     

网络化不确定非线性时滞系统的状态估计

本文研究了离散不确定非线性时滞系统在网络传输不可靠情况下的状态估计问题.针对网络传输丢包问题,采用伯努利(Bernoulli)随机模型,建立了控制信号和输入信号的不可靠传输模型.本文通过状态扩展的方法处理不确定非线性项,得到了扩展状态系统.基于不可靠的控制和测量信息,设计了状态预测器和估计器,并给出相应的误差系统.通过设计最优估计器增益,本文给出了状态预测误差协方差的迭代公式.为了进一步提高状态估计器的精度,设计了一种新型的参数迭代优化方法.针对状态预测误差协方差,本文得到了其稳定性的判别准则.最后,通过一例数值仿真,验证了所得结论的有效性.     

通讯访问约束条件下线性随机系统的状态可估计性

本文从信息论的视角考察了线性离散随机系统在访问约束情况下的可估计性问题.针对系统中存在的访问约束所带来的通讯冲突现象,采用一个二值向量函数描述系统中各个输出信号的通讯状态.针对这类对象,根据由互信息定义的可估计性概念,讨论了访问约束系统的状态估计问题,得出了在输出检测信号传输存在访问约束情况下的状态可估计性条件,解析分析和仿真结果表明,存在合理的通信序列,使得系统在访问约束情况下,能够保持其状态可估计性.本文还证明了在访问约束条件下随机系统的可估计性和相应的确定性系统的能观性之间的等价关系.     

不确定线性系统有限时间状态估计与故障重构

针对具有外部干扰和执行器故障的不确定线性系统,给出了一种有限时间内估计系统状态及重构执行器故障的方法．首先,通过状态和输出等价变换,得到不受执行器故障和建模不确定信息干扰的降维解耦系统．在此基础上设计有限时间状态估计器,并设置任意小的时延参数,实现对降维系统状态的有限时间估计,从而达到对原系统状态有限时间估计的目的;其次,考虑高增益滑模微分器对系统输出微分进行有限时间估计;之后,在原系统状态和系统输出微分有限时间估计的基础上,提出一种对系统不确定信息和执行器故障同时估计的方法;最后,通过对具有执行器故障的F-16飞行器纵向系统模型进行仿真,验证所提方法的有效性．     

切换系统激活模式辨识和有限时间状态估计北大核心CSCD

针对一类具有未知输入的不确定线性切换系统,考虑并利用有限时间观测器解决其激活模式辨识和有限时间状态估计问题。首先,利用状态和输出变换得到解耦未知输入的降维切换系统。其次,为每一个降维子系统设计一个对应的有限时间观测器,并对降维系统与观测器系统输出的残差范数进行最小化,从而提出一种激活模式辨识的方法。然后,通过有限时间观测器设置任意小的时间参数,实现了对降维解耦切换系统的有限时间状态估计,同时利用状态等价变化的方法得到原系统的有限时间状态估计。最后,通过MATLAB仿真验证了所提方法的可靠性。     

基于标准系数法的高度稳定系统信号重构研究

研究了俯仰角和俯仰角速率信号丢失时采用信号重构方法设计飞机高度保持和控制系统;针对线性小扰动飞机模型,设计降维状态观测器实现信号重构,再采用标准系数法设计高度保持和控制回路;通过一个输入信号升降舵偏角和两个输出信号迎角与速度对俯仰角和俯仰角速率进行重构,用标准系数法确定模型中的参数;仿真结果表明对于线性飞机模型用降维状态观测器能够很好地重构俯仰角和俯仰角速率信号,同时标准系数法可使系统达到满意的性能指标。     

线性离散随机系统输入和状态的多步估计方法及应用

具有未知输入的系统的状态估计问题已经在过去几十年里引起了相当的关注.本文对于线性离散随机系统提出了一种基于多步信息的输入和状态同步估计方法.首先,采用多步信息的最小方差方法来获得未知输入.由于引入了包含多个时间步骤的扩张状态和测量向量而计算多步信息,使估计结果与一步估计相比减少了对噪声的敏感性.其次,利用输入估计值和卡尔曼滤波估计过去和当前的状态.该方法在未知输入维数等于状态维数时仍然有良好的估计效果.数值仿真验证了提出的估计方法的有效性.最后,该方法应用于厌氧消化过程反应罐中的溶解甲烷和二氧化碳的浓度估计以验证方法的实用性.     

具有传输延迟的网络控制系统中状态观测器的设计

随着控制系统规模的日益扩大,很多控制系统采用现场总线等技术构成一个控制网 络,这样系统中的很多信息如传感器信号、控制器信号等都通过网络进行传输．由于网络中 通讯带宽的限制、信息的碰撞等原因,不可避免地使信息的传输存在着延迟．本文针对这种 情况,设计了一种能够处理时变延迟的状态观测器,并根据网络负载的不同变化情况,提出 了两种不同的控制策略．通过对一伺服控制系统的实验研究,证实了所提状态观测器和控制 策略的有效性．     

连续大系统的网络结构最优滤波器

本文提出一种连续大系统状态估计器的设计方法--网络结构最优滤波器.这个方法基 于矩阵最小值原理,其计算结果是满足任意结构约束的最优估计.对于分散和递阶结构而言, 此方法具有容错和设计灵活等特点,特别适宜于用多计算机系统来实现,且不要求信道有很宽 的通频带.     

含控制时滞系统的实时故障诊断和最优容错控制

研究含有控制时滞的线性系统的故障诊断方法和最优容错控制问题.给出了最优容错控制律的存在唯一性条件,提出了最优容错控制律的设计算法.通过构造增广的降维状态观测器,设计了在线诊断故障的故障诊断器并同时实现了系统状态的观测,解决了最优容错控制的物理不可实现问题.利用观测器的输出得到物理可实现的动态最优容错控制律.仿真实例验证了故障诊断方法和动态最优容错控制律的有效性.     

Determination of fault operation dynamical constraints for the design of wind turbine DFIG drives

This paper presents an efficient design tool for the estimation of the transient electromagnetic peak torque and transient rotor over-voltages of wind turbines (WT) doubly-fed induction generators (DFIG) during severe fault conditions on the grid side. This versatile and robust tool is well adapted to the implementation in a DFIG drives CAD environment using iterative optimization procedures. In such an application, it is used to compute the dynamical constraints function during the integrated design process of the whole drive including the generator, the gearbox and the power converters. Results show that it is necessary to take into account the dynamical constraints under fault operation, during the early steps of the system design process. Another application of the tool is also illustrated in the paper: the design of the protection system (i.e. the crowbar resistance) for a given generator, a given gearbox and a given power converter.     

存在通信约束和时延的多输入多输出网络控制系统镇定研究

讨论了一类存在通信约束和时延的多输入多输出网络控制系统（NCS）的建模和控制问题.该NCS具有多个传感器和执行器，由于网络通信受限,在同一时刻只能允许部分传感器和执行器访问网络.传感器和执行器访问网络的过程可以用两个马尔可夫链来描述,并且在假设传感器—控制器时延和控制器—执行器时延均为短时延的情况下,将整个闭环NCS建模成一个具有两个模式的马尔可夫切换系统.基于LMI技术和李亚普诺夫方法,给出了闭环NCS随机稳定的充分条件,并给出了状态反馈控制器的设计方法.最后的数值算例验证了所提方法的有效性.     

带非线性等式约束无迹卡尔曼滤波方法

针对带非线性等式约束的非线性系统的状态估计问题,给出了一种新形式的基于无迹卡尔曼滤波及伪观测手段的处理约束的状态估计方法（SPUKF）。在该方法中原动态系统被虚拟地分离成两个并行的子系统,各时刻的状态估计由基于这两个子系统构建的两套滤波链交替得到。相对于伪观测法中的序贯形式估计器,SPUKF无需事先确定观测及约束的处理次序且能获得更好的估计结果,故可以用来解决序贯方法中观测与约束的处理次序问题。由钟摆运动的实例仿真结果看到,SPUKF不仅有好于序贯形式无迹卡尔曼滤波的估计效果,误差改善比达到22%左右,而且算法运行时间与序贯形式估计器相近。此外,其估计效果还与批处理无迹卡尔曼滤波相当。     

Properties of recoverable region and semi-global stabilization in recoverable region for linear systems subject to constraints

This paper investigates linear systems subject to input and state constraints. It is shown that the recoverable region (which is the largest domain of attraction that is theoretically achievable) can be semiglobally stabilized by continuous nonlinear feedbacks while satisfying the constraints. Moreover, when trying to compute the recoverable region, a reduction technique shows that we only need to compute the recoverable region for a system of lower dimension which generally leads to a considerable simplification in the computational effort.     

Power system static state estimation based upon nodal voltages

Static state estimation of a power system based upon measurement of nodal voltages is presented in this paper. Nodal voltages are calculated from a true state by load flow calculation and corrupted deliberately to simulate errors introduced by the telemetry system equipments. These are used as data to state estimation program. The problem of any communication link failure is treated by considering the previous estimation data (bus voltages) of the bus whose communication link has failed in the last estimation. Accuracy of the results from state estimation program are checked by comparison with true state.     

基于动态通信调度的网络化系统最优控制

针对存在介质访问约束的网络化控制系统,研究其中的控制和通信协同设计问题.将网络化控制系统建模为输入矩阵随介质约束而变化的切换系统,运用最优控制理论和切换系统分析方法,设计了可动态调度的最优控制器及实时切换规则,并分析了动态调度下闭环网络化控制系统的稳定性,最后通过仿真验证了该方法的有效性.     

The problem of optimal robust Kalman state estimation via limited capacity digital communication channels

This paper considers a state estimation problem for a continuous-time uncertain system via a digital communication channel with bit-rate constraints. The estimated state must be quantized, coded and transmitted via a limited capacity digital communication channel. Optimal and suboptimal recursive coder–decoder state estimation schemes are proposed and investigated.     

Embedding Relaxations in Global Constraints for Solving TSP and TSPTW

Constraint Programming (CP) has been successfully applied to several combinatorial optimization problems. One of its advantages is the availability of complex global constraints performing efficient propagation and interacting with each other through shared variables. However, CP techniques have shown their limitations in dealing with optimization problems since the link between the objective function and problem decision variables is often quite loose and does not produce an effective propagation. We propose to integrate optimization components in global constraints, aimed at optimally solving a relaxation corresponding to the constraint itself. The optimal solution of the relaxation provides pieces of information which can be exploited in order to perform pruning on the basis of cost-based reasoning. In fact, we exploit reduction rules based on lower bound and reduced costs calculation to remove those branches which cannot improve the best solution found so far. The interest of integrating efficient well-known Operations Research (OR) algorithms into CP is mainly due to the smooth interaction between CP domain reduction and information provided by the relaxation acting on variable domains which can be seen as a communication channel among different techniques. We have applied this technique to symmetric and asymmetric Traveling Salesman Problem (TSP) instances both because the TSP is an interesting problem arising in many real-life applications, and because pure CP techniques lead to disappointing results for this problem. We have tested the proposed optimization constraints using ILOG solver. Computational results on benchmarks available from literature, and comparison with related approaches are described in the paper. The proposed method on pure TSPs improves the performances of CP solvers, but is still far from the OR state of the art techniques for solving the problem. However, due to the flexibility of the CP framework, we could easily use the same technique on TSP with Time Windows, a time constrained variant of the TSP. For this type of problem, we achieve results that are comparable with state of the art OR results.     

Estimating Vehicle State by GPS/IMU Fusion with Vehicle Dynamics

In this paper, a low-cost navigation system with high integrity and reliability is proposed. A high-integrity estimation filter is proposed to obtain a high-accuracy state estimate. The filter utilizes a vehicle velocity constraint measurement to enhance the accuracy of the estimate. Two estimation filters, the extended Kalman filter (EKF) and the extended information filter (EIF), are designed and compared to obtain the estimate of the vehicle state. An instrumentation system that consists of a microcontroller, GPS receiver, IMU, velocity encoder, and Zigbee transceiver is used. The microcontroller provides a vehicle navigation solution at 50 Hz by fusing the measurements of the IMU and GPS receiver using the proposed filter design. Extensive experimental tests are conducted to verify the accuracy of the proposed algorithm. These results are processed with and without the velocity constraints. The estimation accuracy improvement with the addition of the velocity constraints is shown. A more than 16 % reduction in the computational time is demonstrated when using the EIF in comparison to the EKF approach.     

连续系统下的一种容偏估计策略

目标跟踪系统中为降低系统复杂度和保证估计的平稳性常常选择尽可能低阶次的模型, 当目标出现较高阶次的机动时, 则很容易丢失目标. 在假定目标的机动时间与强度均有限时, 提出了容偏估计的思想, 将稳态误差系数约束连同区域极点、估计误差方差上界指标一起构成估计系统的约束指标集, 寻求使得稳态误差系数尽可能小的滤波器, 以使得对机动目标跟踪的系统偏差尽可能小. 通过将约束指标集转化为一组双线性矩阵不等式(BMIs),并利用迭代求解线性矩阵不等式(LMIs)近似BMIs的方法, 得到了满足给定指标约束要求的容偏估计策略, 所设计的容偏估计策略可同时保证估计的准确性和精确性的要求, 从而保证了在目标出现机动时, 估计输出具有尽可能小的系统偏差. 最后数值算例对所提出的结论进行了说明.