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Piezo-actuated vibration disturbance mirror for investigating accelerometer-based tip-tilt reconstruction in large telescopes

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IFAC-PapersOnLine 2016年第21期49卷 361-366页

作者： Glück, Martin Pott, Jörg-Uwe Sawodny, Oliver University of Stuttgart Waldburgstr. 17/19 Stuttgart70563 Germany Königstuhl 17 Heidelberg69117 Germany

The optical performance of large telescopes depends not only on the correction of atmospheric turbulences but also on the suppression of structural vibrations. Nowadays, these disturbances are compensated by Adaptive Optics (AO) systems. Especially for the vibration suppression new control concepts are developed. A well-known method is a state feedback controller. However, for observations with natural faint guide stars the integration time of the wavefront sensor is increased and therefore the bandwidth of the control loop is not sufficient for a fully vibration compensation. Hence, we want to avoid this problem by using an Accelerometer-based Disturbance Feedforward control (DFF), which is independent of the integration time. The vibrations are measured at the relevant telescope mirrors and the tip-tilt modes are reconstructed for the actuator control signals. For investigating the DFF a laboratory setup is built. The setup consists of a classical AO system and additional designed tip-tilt mirrors for simulating and compensating the vibrations. Several accelerometer are mounted at the disturbance mirror. Based on the measured accelerations two position estimators are investigated in order to use them in real telescope applications. © 2016

关键词： Adaptive optics Accelerometers Actuators Atmospheric turbulence Feedforward control Mirrors Signal reconstruction State feedback Structural dynamics Telescopes Vibration measurement Adaptive optics systems estimation algorithm State feedback controller Structural vibrations Telescope applications Vibration compensation Vibration disturbances Vibration suppression

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estimation of the Clutter Correlation Coefficient in Radar Systems

INFOCOMMUNICATIONS JOURNAL

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INFOCOMMUNICATIONS JOURNAL 2016年第3期8卷 8-12页

作者： Popov, Dmitrii I. Smolskiy, Sergey M. Ryazan State Radio Engn Univ Ryazanskaya Oblast Russia Natl Res Univ Moscow Power Engn Inst La Jolla CA USA

estimation of passive interference (so-called, a clutter), which is caused by the point objects, is considered for radar systems. The initial sequence of sampled correlated readings of the point (in distance) target is used as an initial one causing by the antenna beam scanning in a surveillance radar. Basing on the statistical description of this sequence, the likelihood function is introduced and its properties are discussed. An estimation algorithm of the clutter correlation coefficient is synthesized according to the sample of initial correlated readings using the maximal likelihood approach. A structural scheme is given for the correlation coefficient measuring system. The clutter correlation coefficient estimations obtained are asymptotically effective. On the base of the Cramer-Rao equation, the asymptotic formula for a variance of the correlation coefficient is derived, which determines a dependence of estimation accuracy on the value of the correlation coefficient and a number of averaged readings. The formula derived allows provision of necessary estimation accuracy by means of appropriate choice of the averaged reading number. Statistical modeling of the estimation algorithm is described and performed. Modeling results are given, which characterize a dependence of estimation accuracy of the clutter correlation coefficient upon the averaged readings number. A comparison of theoretical and empirical results for estimation accuracy analysis is performed. Statistical modeling results confirm the asymptotical character of the estimation accuracy of the clutter correlation coefficient.

关键词： correlation coefficient clutter estimation algorithm estimation accuracy statistical modeling

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algorithms and Schemes for Chlorophyll a estimation by Remote Sensing and Optical Classification for Turbid Lake Taihu, China

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2015年第1期8卷 350-364页

作者： Zhang, Fangfang Li, Junsheng Shen, Qian Zhang, Bing Wu, Chuanqing Wu, Yuanfeng Wang, Ganlin Wang, Shenglei Lu, Zhaoyi Chinese Acad Sci Inst Remote Sensing & Digital Earth Key Lab Digital Earth Sci Beijing 100094 Peoples R China Minist Environm Protect Satellite Environm Applicat Ctr Beijing 100029 Peoples R China

Monitoring chlorophyll a (CHLA) by remote sensing is particularly challenging for turbid productive waters. Although several empirical and semianalytical algorithms have been developed for such waters, their accuracy varies significantly due to variability in optical properties. In this paper, we evaluated the performance of six CHLA concentration (C-chla) estimation algorithms [e. g., two-band ratio algorithm (TBR), normalized difference chlorophyll index (NDCI), synthetic chlorophyll index (SCI), three-band algorithm (TBS), four-band algorithm (FBS), and improved four-band algorithm (IOC3M)] for a highly turbid lake based on remote sensing reflectance classification. Remote sensing reflectance was classified using the iterative k-mean clustering method. We also developed four estimation schemes (S1-S4) for the six algorithms to assess the effect of the estimation scheme on the accuracy of the algorithms. The estimation schemes were developed based on classification methods (no, soft, or hard classification) and the optimization bands used. The six algorithms performed differently for different remote sensing reflectance classes and different estimation schemes. The optimal algorithms for Classes 1, 2, and 3 were TBS, NDCI, and TBR, respectively. For the four estimation schemes, TBS and NDCI outperformed the other four algorithms. The accuracy of TBS and NDCI was higher than FBS, IOC3M, TBR, and SCI. The accuracy of all six algorithms was improved by remote sensing reflectance classification, particularly for Classes 2 and 3. Soft classification with recalibration of the bands for each class outperformed hard classification for all the three classes.

关键词： Chlorophyll a (CHLA) estimation algorithm Lake Taihu optical classification remote sensing

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Identifiability and Parameter estimation of Linear Continuous-time Systems under Irregular and Random Sampling

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IFAC-PapersOnLine 2015年第28期48卷 332-337页

作者： Mu, Biqiang Guo, Jin Wang, Le Yi Yin, George Xu, Lijian Zheng, Wei Xing Key Laboratory of Systems and Control Chinese Academy of Sciences Beijing100190 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Department of Electrical and Computer Engineering Wayne State University DetroitMI48202 United States Department of Mathematics Wayne State University DetroitMI48202 United States Department of Electrical and Computer Engineering Technology Farmingdale State College State University of New York FarmingdaleNY11735 United States School of Computing Engineering and Mathematics University of Western Sydney PenrithNSW2751 Australia

This paper considers the problem of identifiability and parameter estimation of single-input-single-output, linear, time-invariant, stable, continuous-time systems under irregular and random sampling schemes. Conditions for system identifiability are established under inputs of exponential polynomial types and a tight bound on sampling density. Identification algorithms of Gauss-Newton iterative types are developed to generate convergent estimate sequences. When the sampled output is corrupted by observation noises, input design, sampling times, and convergent algorithms are intertwined. Persistent excitation (PE) conditions for strongly convergent algorithms are derived. Unlike the traditional identification, the PE conditions under irregular and random sampling involve both sampling times and input values. Under the given PE conditions, iterative and recursive algorithms are developed to estimate the original continuous-time system parameters. The corresponding convergence results are obtained. Several simulation examples are displayed to verify the theoretical results. © 2015

关键词： Continuous time systems Iterative methods Lyapunov methods Nonlinear control systems Parameter estimation Sampling convergence and asymptotical normality estimation algorithm Identifiability Irregular sampling Linear continuous time system Non linear least squares

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estimation of the TQ-complexity of chaotic sequences

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IFAC-PapersOnLine 2015年第11 11期48卷 1049-1055页

作者： Makarenko, A.V. Constructive Cybernetics Research Group P.O. Box 560 Moscow101000 Russia Institute of Control Sciences Russian Academy of Sciences Moscow Russia

A new approach is proposed to the quantitative estimation of the complexity of multidimensional discrete sequences in terms of the shapes of their trajectories in the extended space of states. This approach is based on the study of the structural properties of sequences and is suitable for estimating the complexity of both chaotic and stochastic sequences. It is constructed on the method, proposed earlier by the author, of symbolic CTQ-analysis of multidimensional discrete sequences and mappings. The algorithm proposed manipulates not only the frequency of occurrence of symbols, but also takes into account their sequence order. An example (financial time series) is given that demonstrates the application of the tools developed. © 2015

关键词： Time series analysis Chaos theory Computational complexity Digital control systems Discrete time control systems Financial data processing Stochastic systems Chaotic sequence Discrete time systems Discrete sequences estimation algorithm Financial time series New approaches Quantitative estimation Stochastic complexity

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Contraction based identification for nonlinear systems

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IFAC-PapersOnLine 2015年第28期48卷 1190-1195页

作者： Pérez, A. Flores Tang, Yu Grave, Ileana Faculty of Engineering National Autonomous University of Mexico Schulich School of Engineering Av. Universidad 3000 CP. Mexico City Mexico

A top-down approach to identification for systems with nonlinear parameterizations has been recently developed in Flores-Perez et al. (2014, 2015) based on contraction analysis where, at the top-level, the contraction analysis is carried out to ensure the proposed estimation algorithm possess the desired contraction properties, then, at the down-level, the estimation algorithm is realized through a proportional plus integral (PI) form. The realization of estimation schemes however relies on the assumption that state time derivatives are available. In this paper, by filtering signals involved in the system, an alternative to the realization of estimation algorithms without requiring the state time derivatives is given. © 2015

关键词： Parameter estimation Nonlinear analysis Signal processing Contraction theory estimation algorithm estimation schemes Nonlinear parameterization Nonlinear parameterizations Proportional plus integrals Systems identification Top down approaches

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A method for measuring instantaneous treadmill speed

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GAIT & POSTURE 2015年第4期41卷 954-956页

作者： Olson, Nathan M. Klute, Glenn K. Puget Sound Hlth Care Syst Dept Vet Affairs Seattle WA 98108 USA Univ Washington Dept Mech Engn Seattle WA 98105 USA

This paper presents a new method for measuring instantaneous treadmill speed. The method consists of two parts: (1) a motion-capture system and reflective squares placed directly on the treadmill belt, and (2) an algorithm for estimating belt speed and distance traveled from the measured positions of the reflective squares. The method was tested with a single subject walking on an instrumented treadmill. The method is easy to set up and results in an accurate estimate of treadmill speed that is conveniently synchronized with the output of the motion-capture system. Published by Elsevier B.V.

关键词： Treadmill instrumentation Walking speed estimation algorithm

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Adaptive Stabilization of Minimum-Phase Plant under Lipschitz Uncertainty via Yakubovich's Method of Recurrent Objective Inequalities

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IFAC-PapersOnLine 2015年第11 11期48卷 563-567页

作者： Sokolov, Victor F. Department of Mathematics Komi Science Center Russia

This paper addresses a problem of adaptive stabilization of minimum-phase plant under Lipschitz uncertainty and bounded external disturbance. Solution of the problem is based on the method of recurrent objective inequalities proposed by V.A. Yakubovich in the 1960s. This method allows not only to stabilize unknown plant with the use of a simple projection type estimation algorithm, but to ensure online model validation as well. © 2015

关键词： Stabilization Identification (control systems) Robust control Adaptive Control Adaptive stabilization Bounded disturbances estimation algorithm External disturbances Model validation Projection types uncertainty

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Using Singular Value Decomposition for Neutron-Gamma Discrimination

Using Singular Value Decomposition for Neutron-Gamma Discrim...

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Conference on Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments

作者： Linczuk, Maciej Korolczuk, Stefan Cieszewski, Radoslaw Warsaw Univ Technol Inst Elect Syst PL-00665 Warsaw Poland Natl Ctr Nucl Res PL-05400 Otwock Poland

ISBN: (纸本)9781628418804

A Digital Signal Processing method for Neutron Gamma Discrimination [1] is described in this paper. A Singular Value Decomposition (SVD) was used for estimation noiseless signal shape. Based on this shape, detection method was introduced. This method uses projection operation into signal and noise subspace and Signal to Noise Ratio estimation. This method was compared with another one proposed by [2]. Booth method was implemented in MATLAB. Computation was done on signals from scintillators. Data acquisition was dome with high quality hardware. The Neutron Gamma Discrimination algorithm operate on digital samples from ADC converter. Hardware used for data acquisition in this this paper was described in [3]. On the end, the results of this two methods was presented and compared. The signal model in this methods assume additional, white, Gaussian noise.

关键词： SVD - Singular Value Decomposition noise cancelation neutron gamma discrimination estimation algorithm Digital Signal Processing

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Vector Network Analyzer Verification algorithms Using Model with Local Spectrally Selective Components

Vector Network Analyzer Verification Algorithms Using Model ...

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International Siberian Conference on Control and Communications (SIBCON)

作者： Savin, Aleksandr A. Tomsk State Univ Control Syst & Radioelect TUSUR Res Inst Radio Syst Tomsk Russia

ISBN: (纸本)9781479971039

This paper presents verification methods for a calibrated vector network analyzer. The methods are based on a special measurement technique and a model simulating residual errors. Each residual signal has its own unknown frequency properties and known parameters (distance). The properties of the signals are extracted from joint estimation algorithms. Four experiments were performed and verified the proposed methods. Software implemented this methods is also developed.

关键词： verification vector network analyzer (VNA) system model Fourier transform estimation algorithm unscented Kalman filter (UKF) least mean squares (LMS) algorithm

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