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2020 International Instrumentation and Measurement Technology Conference

作者： Belega, Daniel Petri, Dario Politehn Univ Timisoara Dept Measurements & Opt Elect Timisoara Romania Univ Trento Dept Ind Engn Trento Italy

ISBN: (纸本)9781728144610;9781728144603

This paper investigates the effect of frequency uncertainty on the sine-wave amplitude estimator returned by the linear least-square fitting approach when the waveform offset is null. The analytical expressions for the bias and the variance of the amplitude estimator are derived assuming a random sine-wave phase. The derived expressions allow us to analyze the effect of frequency uncertainty on sine-wave amplitude estimator accuracy. Also, the expressions for the mean square errors of the amplitude estimator obtained in the case of pure sine-waves and sine-waves corrupted by additive noise are given. Extensive computer simulations are carried out to verify the theoretical results.

关键词： amplitude estimation discrete Fourier transform least squares algorithm sine-waves statistical analysis

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EFFICIENT IMPLEMENTATION OF SEPARABLE least squares FOR THE IDENTIFICATION OF COMPOSITE LOCAL LINEAR STATE-SPACE MODELS

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IFAC Proceedings Volumes 2005年第1期38卷 184-189页

作者： José Borges Vincent Verdult Miguel Ayala Botto Technical University of Lisbon Instituto Superior Técnico Department of Mechanical Engineering GCAR Avenida Rovisco Pais 1049-001 Lisboa Portugal Delft Center for Systems and Control Delft University of Technology The Netherlands

The efficient implementation of separable least squares identification of nonlinear systems using composite local linear state-space models is discussed in this paper. A full parametrization of system matrices combined with projected gradient search is used to identify the model. This combined approach reduces the number of iterations and improves the numerical condition of the optimization algorithm. Further enhancements result from using numerical tools, e.g. the QR -decomposition, and efficient approaches to compute the separable least squares matrices and gradients of the cost functions. Monte-Carlo simulations are used to show the effectiveness of the proposed approach.

关键词： identification nonlinear systems state-space models least squares algorithm efficient algorithms

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Virtual Inertia Estimation Method of DFIG-based Wind Farm with Additional Frequency Control

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Journal of Modern Power Systems and Clean Energy 2021年第5期9卷 1076-1087页

作者： Pengwei Chen Chenchen Qi Xin Chen Jiangsu Key Laboratory of New Energy Generation and Power Conversion College of Automation EngineeringNanjing University of Aeronautics and AstronauticsNanjingChina

With the increasing penetration of wind power,using wind turbines to participate in the frequency regulation to support power system has become a clear *** accurately quantify the inertia provided by the doubly-fed induction generator(DFIG)based wind farm,the frequency response model of DFIG with additional frequency control is established,and then by using Routh approximation,the explicit expression of the virtual moment of inertia is derived for the DFIG gridconnected *** further enhance the availability of the expression,an estimation method is proposed based on the matrix pencil method and the least squares algorithm for estimating the virtual moment of inertia provided by the wind ***,numerical results tested by a DFIG grid-connected system and a modified IEEE 30-bus system verify the derived expression of the virtual moment of inertia and the proposed estimation method.

关键词： Doubly-fed induction generator(DFIG) additional frequency control virtual moment of inertia matrix pencil method least squares algorithm

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Randomized high order fuzzy cognitive maps as reservoir computing models: A first introduction and applications

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NEUROCOMPUTING 2022年 512卷 153-177页

作者： Orang, Omid de Lima e Silva, Petronio Candido Silva, Rodrigo Guimaraes, Frederico Gadelha Univ Fed Minas Gerais UFMG Machine Intelligence & Data Sci MINDS Lab Belo Horizonte Brazil Fed Inst Northern Minas Gerais IFNMG Januaria Campus Belo Horizonte Brazil Fed Univ Ouro Preto UFOP Dept Comp Sci Ouro Preto Brazil Fed Univ Minas Gerais UFMG Dept Elect Engn Belo Horizonte Brazil

Fuzzy Cognitive Maps (FCMs) have emerged as an interpretable signed weighted digraph method consist-ing of nodes (concepts) and weights which represent the dependencies among the concepts. Although FCMs have attained considerable achievements in various time series prediction applications, designing an FCM model with time-efficient training method is still an open challenge. Thus, this paper introduces a novel univariate time series forecasting technique, which is composed of a group of randomized high order FCM models labeled R-HFCM. The novelty of the proposed R-HFCM model is relevant to merging the concepts of FCM and Echo State Network (ESN) as an efficient and particular family of Reservoir Computing (RC) models, where the least squares algorithm is applied to train the model. From another perspective, the structure of R-HFCM consists of the input layer, reservoir layer, and output layer in which only the output layer is trainable while the weights of each sub-reservoir components are selected ran-domly and kept constant during the training process. As case studies, in this paper we consider solar energy forecasting with public data for Brazilian solar stations, hourly electric load of the power supply company of the city of Johor in Malaysia, solar energy dataset from United States National Renewable Energy Laboratory (NREL), electric load data from the Global Energy Forecasting Competition 2012 (GEFCom 2012), and PJM hourly energy consumption data. The experiments also include the effect of the map size, activation function, the number of order and the size of the reservoir on the accuracy of R-HFCM method. The obtained results confirm the outperformance of the proposed R-HFCM model in comparison to the other methods. This study provides evidence that FCM can be a new way to implement a reservoir of dynamics in time series modeling. The Python code of the model is publicly available for research replication. (c) 2022 Elsevier B.V. All rights reserved.

关键词： Time series forecasting Fuzzy Cognitive Maps Reservoir Computing Echo State Network least squares algorithm

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Convergence of the recursive identification algorithms for multivariate pseudo-linear regressive systems

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INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING 2016年第6期30卷 824-842页

作者： Wang, Xuehai Ding, Feng Jiangnan Univ Key Lab Adv Proc Control Light Ind Minist Educ Wuxi 214122 Peoples R China Henan Univ Urban Construct Sch Math & Phys Pingdingshan 467036 Peoples R China

The performance analysis of the recursive algorithms for the multivariate systems with an autoregressive moving average noise process is still open. This paper analyzes the convergence of two recursive identification algorithms, the multivariate recursive generalized extended least squares algorithm and the multivariate generalized extended stochastic gradient algorithm, for pseudo-linear multivariate systems and proves that the parameter estimation errors consistently converge to zero under persistent excitation conditions. The simulation results show that the proposed algorithms work well. Copyright (C) 2015 JohnWiley & Sons, Ltd.

关键词： parameter estimation least squares algorithm stochastic gradient algorithm pseudo-linear regressive model martingale convergence theorem

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Robust and improved channel estimation algorithm for MIMO-OFDM systems

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2007年第6期6卷 2106-2113页

作者： Zamiri-Jafarian, Hossein Pasupathy, Subarayan Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada Ferdowsi Univ Mashhad Dept Elect Engn Mashhad Iran

Multiple-input multiple-output (MIMO) system using orthogonal frequency division multiplexing (OFDM) technique has become a promising method for reliable high data-rate wireless transmission system in which the channel is dispersive in both time and frequency domains. Due to multiple cochannel interferences in a MIMO system, the accuracy of channel estimation is a vital factor for proper receiver design in order to realize the full potential performance of the MIMO-OFDM system. A robust and improved channel estimation algorithm is proposed in this paper for MIMO-OFDM systems based on the least squares (LS) algorithm. The proposed algorithm, called improved LS (ILS), employs the noise correlation in order to reduce the variance of the LS estimation error by estimating and suppressing the noise in signal subspace. The performance of the ILS channel estimation algorithm is robust to the number of antennas in transmit and receive sides. The new algorithm attains a significant improvement in performance in comparison with that of the regular LS estimator. Also, with respect to mean square error criterion and without using channel statistics, the ILS algorithm achieves a performance very close to that of the minimum mean square error (MMSE) estimator in terms of the parameters used in practical MIMO-OFDM systems. A modification of the ILS algorithm, called modified ILS (MILS), is proposed based on using the second order statistical parameters of channel. Analytically, it is shown that the MILS estimator achieves the exact performance of the MMSE estimator. Due to no specific data sequences being required to perform the estimation, in addition to the training mode, the proposed channel estimation algorithms can also be extended and used in the tracking mode with decision-aided method.

关键词： multiple-input multiple-output (MIMO) channels orthogonal frequency division multiplexing (OFDM) least squares algorithm minimum mean square error channel parameters estimation wireless communications

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Research on model identification and compound control of vibration mirror swing scan system

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MEASUREMENT & CONTROL 2023年第1-2期56卷 420-431页

作者： Du, Xiaoyan Li, Jianying Guo, Xinmin Zhang, Jianlong Harbin Univ Sci & Technol Sch Mech & Power Engn Harbin 150080 Heilongjiang Peoples R China Minist Educ Key Lab Adv Mfg & Intelligent Technol Harbin Heilongjiang Peoples R China Harbin Inst Technol Sch Astronaut Harbin 150001 Heilongjiang Peoples R China

According to the principle of system identification, the least squares algorithm and MATLAB system identification toolbox is used to identify the model of the test bench of the vibration mirror swing scan system with the step signal and the vibration mirror swing-sweep angular displacement as the input and output quantities. Taking the identification model as the object, a sliding mode variable structures composite controller of fuzzy switching gain adjustment is designed. In the controller, according to the actual conditions achieved by the sliding mode, the switching gain is effectively estimated, so as to eliminate the interference of uncertain factors and high-frequency vibration. At the same time, the sliding mode function and sliding mode controller of the system needs to be designed. The switching hyperplane of the system is designed using the fuzzy switching method and the desired dynamic characteristics of the system, to ensure the smooth transition of the system state from outside the hyperplane to the convergence of the switching hyperplane. The simulation results show that: the new composite control method eliminates the shortcomings of PD series control, improves the response speed and tracking accuracy of the vibration mirror swing scan system, and improves the overall performance of the system. And it has a strong ability to inhibit the adverse effects caused by changes in the parameters of the controlled object.

关键词： Vibration mirror swing scan system model identification least squares algorithm sliding mode variable structure fuzzy switching comprehensive performance

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Indirect adaptive periodic control

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 1999年第12期44卷 2308-2312页

作者： Dimogianopoulos, D Lozano, R Ailon, A Univ Technol Compiegne CNRS HEUDIASYC UMR 6599 F-60200 Compiegne France Ben Gurion Univ Negev Dept Elect & Comp Engn IL-84105 Beer Sheva Israel

In this paper, a new indirect adaptive control method is presented. This method is based on a lifted representation of the plant that can be stabilized using a simple performant periodic control scheme. The controller parameters computation involves the inverse of the controllability/observability matrix. Potential singularities of this matrix are avoided by means of an appropriate estimates modification. This estimates transformation is linked to the covariance matrix properties, and hence, it preserves the convergence properties of the original estimates. This modification involves the singular value decomposition of the controllability/observability matrix's estimate. As compared with previous studies in the subject, the controller proposed here does not require the frequent introduction of periodic n-length sequences of zero inputs. Therefore, the new controller is such that the system is almost always operating in closed loop, which should lead to better performance characteristics.

关键词： adaptive control covariance matrix modification least squares algorithm

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Range-based localisation and tracking in non-line-of-sight wireless channels with Gaussian scatterer distribution model

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IET COMMUNICATIONS 2013年第18期7卷 2034-2043页

作者： Banani, Seyed Alireza Najibi, Mahsa Vaughan, Rodney G. Univ Toronto Dept Elect & Comp Engn Toronto ON Canada Simon Fraser Univ Sch Engn Sci Burnaby BC V5A 1S6 Canada

Range-based localisation and tracking methods use the time-of-arrival (TOA) between the mobile station and several base stations, but the multipath propagation of non-line-of-sight channels complicates the estimation and processing. For channel modelling, the Gaussian scatterer distribution model has been reported to have a reasonable match between its TOA probability density distribution (PDF) and measured TOA data. In this study, this TOA PDF is adapted, along with selection from multiple motion models of the mobile station, for a new location and tracking algorithm. Since the TOA PDF is non-Gaussian and is a non-linear function of the position of the mobile, particle filtering is used which increases the complexity of the algorithm. The focus is on the tracking performance, and this is evaluated by simulation using idealised statistical channels, allowing direct comparison between different location algorithms. In this context, the presented algorithm is more accurate than the benchmarks of extended Kalman filter tracking, and positioning using least squares.

关键词： electromagnetic wave scattering Gaussian distribution nonlinear functions particle filtering (numerical methods) probability radio tracking radionavigation radiowave propagation time-of-arrival estimation wireless channels least squares algorithm extended Kalman filter tracking idealised statistical channels particle filtering nonlinear function multiple motion models TOA PDF multipath propagation base stations mobile station TOA probability density distribution time-of-arrival estimation Gaussian scatterer distribution model range-based tracking method nonline-of-sight wireless channels range-based localisation method

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High precision Fast Line Detection of alignment and coupling for planar Optical Waveguide device

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OPTIK 2017年 145卷 519-528页

作者： Zheng, Yu Xia, Bingxin Cent S Univ Coll Mech & Elect Engn High Performance Complex Mfg Changsha 410083 Hunan Peoples R China

Machine vision is widely used in alignment between planar optical waveguide chip and optical fiber array. Optical component edge detection is one of the key steps of machine vision in alignment. This paper has proposed a line detection algorithm based on the progressive probabilistic Hough transform (PPHT) and iteratively reweighted least squares (IRLS) algorithm for alignment between planar optical waveguide chip and optical fiber array. The experiment results show that the detection angle error is less than 0.005 degrees and the time consumption is less than 0.5 s through the proposed algorithm. Besides, it also can accurately fit optical component edge with some non-random factors. Therefore, the proposed new algorithm has the advantages of high precision, fast computing speed and good robustness, and it can successfully realize the high-precision fast line detection of optical component edge. (C) 2017 Elsevier GmbH. All rights reserved.

关键词： Alignment and coupling Hough transform least squares algorithm Line detection Planar optical waveguide device

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