一种改进的一致性数据融合算法

针对目前数字滤波算法中存在对先验信息要求苛刻及定义数据间支持度中门限的预先设定问题,在基于测量方差加权算法基础上,引入相对距离和置信距离的思想对其次优融合估计结果进行改进。仿真结果直观地说明了该估计算法的有效性。     

我国90年代陆基遥感定位测试研究的初步分析

从光学遥感、微波遥感、大气遥感等方面对我国90年代陆基遥感测试研究工作进行回顾。研究工作表明,陆基遥感测试研究对空基遥感信息的分析和应用是不可缺少的基础性工作,对提高遥感信息应用的定量化水平有着重要作用。分析中也得出陆基遥感测试研究存在的问题,主要表现在陆基遥感测试的频度和稳定程度较低,需要在时间和空间维上加强陆基遥感测试工作,为空基遥感信息的定量分析提供有效的地面数据支持。     

基于PMU实测摇摆曲线的暂态稳定量化分析

提出了用扩展等面积准则(EEAC)评估相量测量装置(PMU)实测摇摆曲线的稳定裕度的方法。EEAC已被广泛用于分析电力系统的稳定域和优化稳定控制的决策。当受扰轨迹来自仿真时，所用的模型、参数和扰动场景很可能与实际不符。PMU给出的受扰轨迹克服了这个缺点，若能使主导映象的识识及稳定裕度的计算也不依赖于数学模型和参数，就可以真实反映实际系统的暂态稳定裕度。虽然PMU量测不能反映假想的场景，不支持对控制量的决策，但评估实际轨迹的稳定裕度仍有很大意义。仿真表明，所提出的算法在系统模型和参数未知的情况下，可以快速而精确地评估PMU实测摇摆曲线的稳定裕度。     

Optimal control with constrained total variance for Markov jump linear systems with multiplicative noises

We consider in this paper the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noises (MJLS-mn for short). Our objective is to present an optimal policy for the problem of maximising the system's total expected output over a finite-time horizon while restricting the weighted sum of its variance to a pre-specified upper-bound value. We obtain explicit conditions for the existence of an optimal control law for this problem as well as an algorithm for obtaining it, extending previous results in the literature. The paper is concluded by applying our results to a portfolio selection problem subject to regime switching.     

Comparison of a district heating system operation based on actual data – Omsk city,Russia, case study*

A district heating (DH) system in the Russian city of Omsk has been considered as a case study. This study is based on the data set of temperature and demand recorded over two-year operation of the DH system. We provide an insight on how the heat demand profile is met by the control framework. The paper quantifies the DH system performance by using heat load curves, maximum, minimum and average values of temperature, paving the way for a modelling approach. Central heating process in Omsk in 2017 was generally smoother than in 2016, while peak values are also lower. In 2017, its supply temperature was about 5°C closer to the control curve. The dispersion of the points was reduced between 2016 and 2017, especially at higher outdoor temperatures. Further lowering annual and peak heat demand, which are respectively 4% and 9% lower in 2017 should be a priority in future.     

Polynomial filtering for nonlinear stochastic systems with state‐ and disturbance‐dependent noises

This article is concerned with the polynomial filtering problem for a class of nonlinear stochastic systems governed by the Itô differential equation. The system under investigation involves polynomial nonlinearities, unknown‐but‐bounded disturbances, and state‐ and disturbance‐dependent noises ((x,d)‐dependent noises for short). By expanding the polynomial nonlinear functions in Taylor series around the state estimate, a new polynomial filter design method is developed with hope to reduce the conservatism of the existing results. In virtue of stochastic analysis and inequality technique, sufficient conditions in terms of parameter‐dependent linear matrix inequalities (PDLMIs) are derived to guarantee that the estimation error system is input‐to‐state stable in probability. Moreover, the desired polynomial matrix can be obtained by solving the PDLMIs via the sum‐of‐squares approach. The effectiveness and applicability of the proposed method are illustrated by two numerical examples with one concerning the permanent magnet synchronous motor.     

Use of a quantile regression based echo state network ensemble for construction of prediction Intervals of gas flow in a blast furnace

The usual huge fluctuations in the blast furnace gas (BFG) generation make the scheduling of the gas system become a difficult problem. Considering that there are high level noises and outliers mixed in original industrial data, a quantile regression-based echo state network ensemble (QR-ESNE) is modeled to construct the prediction intervals (PIs) of the BFG generation. In the process of network training, a linear regression model of the output matrix is reported by the proposed quantile regression to improve the generalization ability. Then, in view of the practical demands on reliability and further improving the prediction accuracy, a bootstrap strategy based on QR-ESN is designed to construct the confidence intervals and the prediction ones via combining with the regression models of various quantiles. To verify the performance of the proposed method, the practical data coming from a steel plant are employed, and the results indicate that the proposed method exhibits high accuracy and reliability for the industrial data. Furthermore, an application software system based on the proposed method is developed and applied to the practice of this plant.     

General equivalence between two kinds of noise-correlation filters

A recent comment (Chang, 2014) theoretically demonstrated that for the linear system with the correlated process and measurement noises, the GASF framework proposed in the paper Wang et al. (2012) was equivalent to the conventional de-coupling filtering framework. In this note, we would further show that such equivalence between the two frameworks can be justified in a more general way, even for the nonlinear system.     

基于实测数据的沉降预测方法综述

介绍了静态和动态两种基于实测数据的沉降外推预测方法,阐述了各种方法的适用范围和优缺点,指出基于实测数据的沉降预测法是针对建筑实测所得的离散沉降值,用数学模型预测地基的最终沉降量,具有较好的适用性。     

减小声光频谱仪频率测量方差算法研究

声光器件衍射光峰值偏转位置与输入信号频率成正比是声光频谱仪测频的基本原理,但实际中衍射的非线形效应会引起衍射光峰值偏转误差较大。为减小频率测量方差,需对衍射光强数据做相应处理。对CCD背景噪声的数字特征分析,以背景噪声数学平均值为阈值做去噪处理。根据最小二乘法原理,对衍射光强数据做一次高斯函数拟合,拟合数据与光强数据相关系数为0.997 6。在现有测试光学平台下,根据衍射光强峰值位置估计的频率测量方差为542.5 kHz2,利用拟合高斯函数中心值估计的频率测量方差为31.8 kHz2。为减小声光频谱仪频率测量方差提供了理论支持。