Estimation of the cortical connectivity patterns during the intention of limb movements.

The problem of the definition and evaluation of brain connectivity has become a central one in neuroscience during recent years as a way to understand the organization and interaction of cortical areas during the execution of cognitive or motor tasks. In this article, we propose the use of the directed transfer function (DTF) method on cortical signals estimated from high-resolution electroencephalography (EEG) recordings. An application of the proposed technique to the estimation of the cortical connectivity pattern in normal subjects and in one spinal-cord-injured patient is also provided.     

计及PMU支路电流相量的状态估计模型

评述了相量量测在电力系统状态估计中的各种应用模型,包括仅采用相量测量装置(PMU)的量测进行线性估计、在非线性估计中加入PMU电压幅值和相角量测,以及把非线性估计和线性估计结合等方案.把PMU量测值直接作为估计值虽然可以降低估计的维数,但不一定有利于估计精度.当前PMU的配置还难以满足可观性要求,故必须将PMU量测与其他量测一起用于状态估计.但在非线性估计中,很难直接利用PMU支路电流量测,特别是其相角量测.文中提出通过量测变换来计及PMU支路电流幅值和相角量测的模型.对各种非线性估计模型的仿真说明该模型的估计精度优于其他方案.     

混合量测用于电力系统状态估计

根据目前PMU的配置状况和PMU与SCADA的数据特点,提出了一种基于PMU与SCADA混合量测的状态估计方法。该方法将非线性估计结果作为伪量测量加入线性估计中,并根据平均距离动态地调整伪量测量的权值,然后通过插值对非线性可观测区域进行实时的近似估计。最后通过IEEE14、IEEE57系统进行了仿真。仿真表明即使在PMU配置较少的情况下,该方法亦能够有效改进非线性可观测区域状态估计的精度和刷新速度。该方法兼顾了PMU和SCADA的特点,有较好的应用价值。     

Transient security assessment using multivariate polynomial approximation

This paper presents an efficient method for transient security assessment. The proposed method exploits the computational efficiency of linear estimation methods to determine an accurate nonlinear mapping function. The novelty of the proposed method is that a nonlinear transformation is applied to the original variables, voltage magnitudes and phase angles, so that the mapping function is approximately linear in terms of the transformed variables. The linear function obtained using the transformed variables is indeed nonlinear in terms of original variables. The attractiveness of this method is that the estimated function is not a linearized approximation although a linear estimation method is used. The potential of the proposed method is demonstrated using the New England 39-bus system and a larger power system with 470 buses.     

基于混合量测的二次线性状态估计方法及其工程应用

基于相量测量单元(PMU)和数据采集与监控(SCADA)混合量测进行状态估计计算时,如果仍采用传统非线性估计模型,将面临PMU量测计算权值难以确定、PMU量测坏数据辨识不准、相角参考点和成熟商用程序改动等多方面问题。提出了一种基于混合量测的二次线性状态估计方法。该方法在传统非线性状态估计收敛后,利用其结果中的各节点电压幅值及相角估计值和PMU相量量测再进行二次线性状态估计计算,有效解决了上述问题。最后结合电网实例验证了该方法的有效性。     

Takagi-Sugeno tracking control of a fermentation process with respect to asymmetric constraints

This article deals with the tracking problem for nonlinear biological process with asymmetric constraints on the controller. Using the fuzzy logic Takagi-Sugeno (TS), the nonlinear process is modeled by a fuzzy model and a parallel distributed compensation (PDC) controller with respect asymmetric constraints is designed. The main contribution of this work is to extend the available results, in the context of a TS formulation, for symmetrical constraints to asymmetrical ones. Hence, sufficient conditions are obtained for the first time, in terms of linear matrix inequalities (LMIs), for the existence of an asymmetrical constrained PDC controller. Moreover, fuzzy observer based controller with unmeasured premise variables is designed. The performance and effectiveness of the method are illustrated in simulation by considering a fermentation process.     

Perceptualization of biomedical data. An experimental environmentfor visualization and sonification of brain electrical activity

Complex experiments require sophisticated visualization of a large number of parameters. However, physiological characteristics of human perception limit the number of visualized parameters and their dynamics. Multimodal data presentation could increase throughput, introduce new data streams, and improve temporal resolution. The future of biomedical data presentation will probably be marked with multimodal data presentation and integration of multiple diagnostic procedures. Here, the authors present sonification as a second presentation modality. During analysis, multimodal parameters must be set to maximize the distance of changes in the perceptual domain. The authors implemented sonification in their 3D EEG visualization environment to render synesthetic extension of a selected data channel or to introduce new composite parameters. Sonification improved the ability to assess genuine dynamics of brain electrical activity and to perceive inherent spatio-temporal patterns of brain electrical activity     

Brain Network Analysis From High-Resolution EEG Recordings by the Application of Theoretical Graph Indexes

The extraction of the salient characteristics from brain connectivity patterns is an open challenging topic since often the estimated cerebral networks have a relative large size and complex structure. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach would extract significant information from the functional brain networks estimated through different neuroimaging techniques. The present work intends to support the development of the “brain network analysis:” a mathematical tool consisting in a body of indexes based on the graph theory able to improve the comprehension of the complex interactions within the brain. In the present work, we applied for demonstrative purpose some graph indexes to the time-varying networks estimated from a set of high-resolution EEG data in a group of healthy subjects during the performance of a motor task. The comparison with a random benchmark allowed extracting the significant properties of the estimated networks in the representative Alpha (7–12 Hz) band. Altogether, our findings aim at proving how the brain network analysis could reveal important information about the time-frequency dynamics of the functional cortical networks.      

Multimodal Nonlinear Optical Microscopy and Applications to Central Nervous System Imaging

Multimodal nonlinear optical (NLO) imaging is poised to become a powerful tool in bioimaging given its ability to capitalize on the unique advantages possessed by different NLO imaging modalities. The integration of different imaging modalities such as two-photon-excited fluorescence, sum frequency generation, and coherent anti-Stokes Raman scattering on the same platform can facilitate simultaneous imaging of different biological structures. Parameters to be considered in constructing a multimodal NLO microscope are discussed with emphasis on achieving a compromise in these parameters for efficient signal generation with each imaging modality. As an example of biomedical applications, multimodal NLO imaging is utilized to investigate the central nervous system in healthy and diseased states.     

基于KPCR的发电机组参数预测与估计

为了解决机组运行过程中参数失效和优化过程中参数计算的问题,提出了基于核回归(KPCR)的发电机组参数预测和估计方法。首先用正常数据建立机组参数的预测和估计模型,确定各变量之间的回归关系,然后将其用于参数的在线预测与估计。该方法可以有效地捕捉变量间的非线性关系,参数预测和估计效果明显好于偏最小二乘回归(PLS)和主元回归(PCR)等线性回归方法。某电厂1000 MW发电机组烟气含氧量历史特征数据集仿真试验证明了该方法的有效性。     

基于线性矩阵不等式的磁悬浮轴承多目标控制系统设计

首先建立了磁悬浮轴承局部子系统线性Takagi- Sugeno(TS)模糊模型，利用单点模糊化、乘积推理和加权平均得到整个系统的非线性模型。针对以往非线性系统的单目标控制设计，提出了基于线性矩阵不等式(LMI)的多目标模糊控制系统的设计方法。该方法将闭环控制系统的稳定性、抗干扰性及极点配置的要求统一到1个线性矩阵不等式组中，通过求解线性矩阵不等式组获得满足要求的控制器参数，利用并行分布补偿控制(PDC)方法得到整个系统的非线性模糊状态反馈控制器，实现了系统同时满足多目标的要求，并且避免了设计过程的多次反复。应用于磁悬浮轴承非线性系统的控制中，通过实验验证了该设计方法的有效性。     

A car test for the estimation of GPS/INS alignment errors

Misalignment can be an important error source in the integration of the global positioning system (GPS) and inertial navigation systems. This paper presents car test results on the estimation of alignment errors in the integration of a low-grade inertial measurement unit (IMU) with accurate GPS measurement systems. The car test was conducted with a low-cost solid-state IMU and carrier-phase differential GPS measurement systems. Test results showed that changes in the angular velocity improve the estimation of the lever arm between the GPS antenna and IMU. They also showed that changes in acceleration improve the estimation of the relative attitude between the GPS antenna array and IMU. The lever arm was estimated with a 10-cm error. The relative attitude was estimated with a half-degree error. An iterative scheme was used to improve the estimation of the alignment errors during postprocessing. The scheme was shown to be useful when the test car could not have sufficient changes in motion due to limitations in its path. With the given set of test data, the estimation error decreased as the number of iterations increased.     

基于核偏最小二乘的电厂热力参数预测与估计*

为了解决机组运行过程中参数失效和优化过程中参数计算的问题,提出了一种基于核偏最小二乘方法的热力参数预测和估计方法。首先用正常数据建立机组参数的预测和估计模型,确定各变量之间的回归关系,然后将其用于参数的在线预测与估计。其基本思想是通过非线性核函数将数据映射到高维特征空间,然后在高维特征空间中进行偏最小二乘回归运算。该方法可以有效地捕捉变量间的非线性关系,参数预测和估计效果明显好于偏最小二乘法和主元回归方法等线性回归方法。某1 000 MW发电机组烟气含氧量历史特征数据集仿真试验及实际应用比对实验证明了该方法的有效性。     

基于非线性回归分析的特高压 直流线路杆塔质量计算

在输电线路设计方案比选及优化中,需要随时调用杆塔费用指标(或杆塔质量指标)。通常估算杆塔质量（下称塔重）的方法是在已有施工图设计塔重的基础上,只对塔型的一种呼高进行计算,而同一型式的其他呼高或另外荷载条件下的塔重,则用公式近似估算,其误差大,操作繁琐,因此需提出简单实用的新型塔重估算模型。采用“±800 kV铁塔典设”的塔型塔重作为数据样本,以非线性多元回归分析理论为依据建立数学模型,使用仿真软件Matlab对样本数据进行计算和分析,从而得到铁塔质量与杆塔呼高、荷载条件等的数学关系式。由该式得出的估算塔重结果分别与实际典设塔重和哈郑线设计标段总塔重作比较,其误差小、精度高、实用有效,对于设计方案比选及优化是可以接受的。     

Luenberger-type cubic observers for state estimation of linear systems

This article introduces a new nonlinear observer for state estimation of linear time invariant systems. The proposed observer contains a (nonlinear) cubic term to enhance observer response. Unlike previously proposed observers, the cubic observer has nonlinear estimation error dynamics. Convergence criteria, performance advantages, and observer-based feedback control with cubic observers are addressed. Simulation examples demonstrating performance improvement compared with linear observers, are included.     

多采样周期混合量测环境下的主动配电网状态估计方法

针对主动配电网中远程终端单元(RTU)、相量测量单元(PMU)与高级量测体系(AMI)多采样周期量测数据长期共存的实际情况,提出了一种基于RTU,PMU,AMI混合量测的主动配电网状态估计混合算法。该混合算法由非线性静态状态估计、线性静态状态估计与线性动态状态估计3种算法组成。线性动态状态估计与线性静态状态估计利用PMU量测与RTU量测,实时跟踪系统注入节点有功功率与无功功率的变化,在非AMI量测的采集时刻,为非线性静态状态估计提供高精度的虚拟量测。所提算法缩短了非线性静态状态估计的计算周期,提高了非线性静态状态估计的精度,提升了对主动配电网运行状态的预测能力。通过算例仿真,验证了所提算法的有效性。     

Extracting Low-Frequency Spatio-Temporal Patterns in Ambient Power System Data Using Blind Source Separation

Wide-area techniques provide a powerful tool to extract spatio-temporal patterns from high-dimensional datasets and can be used for event detection and visualization, data fusion, stability assessment, and coherency analysis. In this paper, a novel blind source separation-based approach for extracting low-frequency spatio-temporal patterns from measured ambient power system data is proposed and a spatio-temporal visualization index is also suggested. This methodology combines a nonlinear hierarchical neural network with a Blind Source Separation (BSS) technique. The neural network allows reducing noise and removing the nonlinear relations among data (preserve dynamic features of interest), while the BSS technique permits extracting spatial and temporal patterns. In addition, the proposed approach takes advantage of the latest techniques in nonlinear estimation of non-stationary time series. Finally, application examples of the proposed framework on real test cases recorded from an actual power system by Phasor Measurement Units (PMUs) are presented. The obtained results show that the temporal patterns can be used for extracting and identifying the low-frequency oscillation modes and the spatial patterns can be used for identifying modes with the most contribution in original data. Compared to other BSS approaches, the proposed method has shown to be better for the analysis of real ambient data.     

Identification in nonlinear systems by using an automatic choosing function and a genetic algorithm

This paper deals with an identification method based on an automatic choosing function (ACF) for nonlinear systems. A full data region or an entire domain is partitioned into subdomains and the unknown nonlinear function to be estimated is approximately described by a linear equation on each subdomain. These linear equations are smoothly united into a single expression by the ACF, and the resulting model is linear in its parameters. Hence these parameters are easily evaluated by the linear least-squares method. The subdomains and the ACF are properly determined by a genetic algorithm that has a high potential for global optimization. Numerical experiments demonstrate the effectiveness of the proposed method. © 1998 Scripta Technica, Electr Eng Jpn, 125(4): 43–51, 1998