A robust estimation approach for uncertain systems with perturbed measurements

This paper deals with state estimation problem for uncertain continuous‐time systems. A numerical treatment is proposed for designing interval observers that ensures guaranteed upper and lower bounds on the estimated states. In order to take into account possible perturbations on the system and its outputs, a new type of interval observers is introduced. Such interval observers consist of two coupled general Luenberger‐type observers that involve dilatation functions. In addition, we provide an optimality criterion in order to find optimal interval observers that lead to tight interval error estimation. The proposed existence and optimality conditions are expressed in terms of linear programming. Also, some illustrative examples are given. Copyright © 2015 John Wiley & Sons, Ltd.     

Recursive state estimation for discrete‐time nonlinear systems with event‐triggered data transmission,norm‐bounded uncertainties and multiple missing measurements

In this paper, we consider the recursive state estimation problem for a class of discrete‐time nonlinear systems with event‐triggered data transmission, norm‐bounded uncertainties, and multiple missing measurements. The phenomenon of event‐triggered communication mechanism occurs only when the specified event‐triggering condition is violated, which leads to a reduction in the number of excessive signal transmissions in a network. A sequence of independent Bernoulli random variables is employed to model the multiple measurements missing in the transmission. The norm‐bounded uncertainties that could be considered as external disturbances which lie in a bounded set. The purpose of the addressed filtering problem is to obtain an optimal robust recursive filter in the minimum‐variance sense such that with the simultaneous presence of event‐triggered data transmission, norm‐bounded uncertainties, and multiple missing measurements; the filtering error is minimized at each sampling time. By solving two Riccati‐like difference equations, the filter gain is calculated recursively. Based on the stochastic analysis theory, it is proved that the estimation error is bounded under certain conditions. Finally, two numerical examples are presented to demonstrate the effectiveness of the proposed algorithm. Copyright © 2016 John Wiley & Sons, Ltd.     

Design and Comparison Base Analysis of Adaptive Estimator for Completely Unknown Linear Systems in the Presence of OE Noise and Constant Input Time Delay

In this paper, an adaptive estimator (AE) is introduced to learn the approximate Q‐function and control policy by only using the noisy states and control signals of the unknown linear, discrete time systems having constant input time delay. The system measurements are uncertain owing to output error (OE)‐type noise acting randomly on the system measurements. Therefore, this research differs from the designed AE in the literature since previous research ignores the role of the external random disturbances on AE‐based learning. In order to compare the AE‐based learning results with traditional system identification (SI) approaches, a modified version of the OE model structure for unstable systems is reviewed and parameters of a second‐order unstable system with constant input time delay are identified. The simulation results demonstrate that the designed AE efficiently minimizes the stochastic cost function and the temporal difference error by learning the approximate solution for the Hamilton‐Jacobi‐Bellman (HJB) equation. It is noted that the error in the Q‐function obtained with the AE is slightly larger than the Q‐function attained with the identified OE parameters. However, as the noise standard deviation increases, the error in the AE‐based learning results reduces whereas the error in the OE‐based learning increases. This indicates that even though the added random noise deteriorates the performance of the OE predictor, it improves the learning efficiency of the AE since it acts like exploration noise.     

state estimation with fading measurements,randomly varying nonlinearities and probabilistic distributed delays

In this paper, the state estimation problem is investigated for a class of discrete‐time stochastic systems in simultaneous presence of three network‐induced phenomena, namely, fading measurements, randomly varying nonlinearities and probabilistic distributed delays. The channel fading is characterized by the ?th‐order Rice fading model whose coefficients are mutually independent random variables with given probability density functions. Two sequences of random variables obeying the Bernoulli distribution are utilized to govern the randomly varying nonlinearities and probabilistic distributed delays. The purpose of the problem addressed is to design an state estimator such that the dynamics of the estimation errors is stochastically stable and the prespecified disturbance rejection attenuation level is guaranteed. Through intensive stochastic analysis, sufficient conditions are established under which the addressed state estimation problem is recast as a convex optimization one that can be solved via the semi‐definite program method. Finally, a simulation example is provided to show the usefulness of the proposed state estimation scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

Experimental investigation of velocity fluctuations in a radial diffuser pump

The strong interaction in a radial pump due to the relative movement between the impeller and the diffuser may excite not only strong pressure fluctuations but also velocity fluctuations. In this paper, the laser Doppler velocimetry(LDV) technique is successfully applied to measure the periodic flow field in a radial diffuser pump with low-specific speed, in order to investigate the velocity fluctuations caused by the impeller-diffuser interactions both in the impeller and diffuser regions. The velocity fluctuations in the impeller region are quantitatively examined at different radial positions, and the flow structure at the radial gap between two flow components is analyzed at different relative positions. In addition, the downstream effect on the diffuser flow is quantitatively and qualitatively assessed and compared with the turbulence effect.     

An introduction to the Information Display Measurement Standard 1, the first display measurement standard from the International Committee for Display Metrology

On June 1, 2012, the Information Display Measurement Standard version 1 was released. This is the first standard from the worldwide standard group, the International Committee for Display Metrology, a standards committee within SID, and it culminates several years worth of development from many contributors at various levels. It has 26 top‐level chapters and a total over 450 sections of all parts, including over 200 measurement sections and 8 appendices that cover 133 topics of display metrology, tutorials, technical discussions, and references. Herein is an overview of the Information Display Measurement Standard version 1, including the structure of the document, tips, tricks, and hidden features, how it is maintained, support material, a breakdown of its contents, and finally, a sampling of four of the over 200 measurements. The standard is available as a free download and can be found on the International Committee for Display Metrology home page — http://www.icdm‐sid.org .     

NetCluster: A clustering-based framework to analyze internet passive measurements data

Internet measured data collected via passive measurement are analyzed to obtain localization information on nodes by clustering (i.e., grouping together) nodes that exhibit similar network path properties. Since traditional clustering algorithms fail to correctly identify clusters of homogeneous nodes, we propose the NetCluster novel framework, suited to analyze Internet measurement datasets. We show that the proposed framework correctly analyzes synthetically generated traces. Finally, we apply it to real traces collected at the access link of Politecnico di Torino campus LAN and discuss the network characteristics as seen at the vantage point.     

Path Loss Modelling for Location Service Applications

The aim of this paper is the path loss modelling for the radiolocation services in radio communication networks, particularly in cellular networks. The main results of the measurements obtained in the physical layer of the UMTS are introduced. A new method for the utilization of the multipath propagation phenomenon to improve the estimation of the distance between the MS （mobile station） and the BS （base station） is outlined. This method significantly increases the quality of location services in systems which use a radio interface with DS （direct sequence） CDMA （code division multiple access）.     

基于光纤传感器的转速测量系统设计

本文提出一种基于光纤传感器测量旋转轴转速的方法,入射光线经旋转轴反射面反射后,利用反射式光纤传感器采集得到强弱变化的反射光,采用频率测量法得到反射频率,通过信号处理电路进行转换,即可测量转速.该系统具有电路结构简单、精度高、抗干扰能力强、光路弯曲、测量方便等优点.