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recursive least squares algorithm for Nonlinear Dual-rate Systems Using Missing-Output Estimation Model

CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2017年第4期36卷 1406-1425页

作者： Chen, Jing Liu, Yanjun Wang, Xuehai Jiangnan Univ Sch Internet Things Engn Key Lab Adv Proc Control Light Ind Minist Educ Wuxi 214122 Peoples R China

In this paper, a recursive least squares algorithm is proposed for a class of nonlinear dual-rate systems. By using the missing-output estimation model, the unavailable outputs can be estimated. Then, the unknown parameters can be estimated from all the inputs and outputs. Compared with the polynomial transformation technique and the lifting technique, the unknown parameters can be estimated directly by using the missing-output estimation model, without increasing the number of parameters. The convergence analysis and the simulation results indicate that the proposed method is effective.

关键词： Parameter estimation recursive least squares algorithm Missing-output estimation model Martingale convergence theorem Nonlinear system

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A New Formalism of the Sliding Window recursive least squares algorithm and Its Fast Version

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2011年第6期E94A卷 1394-1400页

作者： Nishiyama, Kiyoshi Iwate Univ Fac Engn Dept Elect Engn & Comp Sci Morioka Iwate 0208551 Japan

A new compact form of the sliding window recursive least squares (SWRLS) algorithm, the I-SWRLS algorithm, is derived using an indefinite matrix. The resultant algorithm has a form similar to that of the traditional recursive least squares (RLS) algorithm, and is more computationally efficient than the conventional SWRLS algorithm including two Riccati equations. Furthermore, a computationally reduced version of the I-SWRLS algorithm is developed utilizing a shift property of the correlation matrix of input data. The resulting fast algorithm reduces the computational complexity from O(N-2) to O(N) per iteration when the filter length (tap number) is N. but retains the same tracking performance as the original algorithm. This fast algorithm is much easier to implement than the existing SWC FTF algorithms.

关键词： recursive least squares algorithm sliding window forgetting factor fast algorithm system identification adaptive filter

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Bi-loop Matrix Forgetting Factor-Based Coupled recursive least squares algorithm for Identification of Multivariable Plants

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JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS 2018年第2期29卷 136-152页

作者： Mirhoseini, Parvin Tabatabaei, Mohammad Islamic Azad Univ Khomeinishahr Branch Dept Elect Engn Esfahan Iran

In this study, a new parameter estimation method based on coupled least squares method for recursive estimation of time-varying parameters in multivariable systems is presented. The bi-loop matrix forgetting factor-based coupled recursive least squares method is employed for estimation of time-varying parameters in which the forgetting factor for each parameter is adjusted according to its variance. This means that the forgetting factors of slow-varying and fast-varying parameters are calculated according to their variances, automatically. The simulation results demonstrate the advantage of the proposed method for estimation of parameters with different variation rates (including slow-varying or fast-varying parameters) in comparison with ordinary coupled least squares method.

关键词： System identification recursive least squares algorithm Coupled least squares algorithm Multivariable systems Time-varying parameters Matrix forgetting factor

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Global convergence of adaptive IIR filter with recursive least squares algorithm

Global convergence of adaptive IIR filter with recursive lea...

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3rd International Conference on Signal Processing (ICSP 96)

作者： Wang, HK Taiyuan University of Technology Taiyuan China

ISBN: (纸本)7505338900

The application of a recursive least squares algorithm to adaptive infinite impulse response (IIR) filters is investigated in this paper. A global convergence of an adaptive IIR filter is developed. It is shown that the noll solutions of the parameter error vector, filtered error and output error in the filter are asymptotically stable for a stable reference signal. The analysis proceeds with simple algebra, does not rely on the commonly used hyperstability, strictly passive machinery and lower bounded input. The simulation results are also included to demonstrate the behaviours of the filter.

关键词： IIR filters adaptive filters adaptive signal processing recursive filters least squares approximations convergence of numerical methods adaptive IIR filter recursive least squares algorithm infinite impulse response filters global convergence parameter error vector filtered error output error stable reference signal simulation results

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Modified recursive least squares algorithm for Sparse System Identification 7

Modified Recursive Least Squares Algorithm for Sparse System...

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7th International Conference on Modelling, Identification and Control (ICMIC)

作者： Wang, Yanpeng Li, Chunming Tian, Caixia Hebei Univ Sci & Technol Sch Informat Sci & Engn Shijiazhuang Hebei Peoples R China

ISBN: (纸本)9780956715753

To adapt to the sparsity of some sparse systems in system identification, a novel modified recursive least squares algorithm is proposed. This algorithm utilizes the output error to control the value of forgetting factor, which deals with the contradiction between convergence rate and stationary misadjustment. In addition, through the introduction of zero attractor in parameters' iterations, the proposed algorithm improves the convergence rate of zero and near-zero parameters dominating sparse systems. The simulation results indicate that the algorithm proposed in this paper can effectively strengthen the accuracy of sparse system identification.

关键词： recursive least squares algorithm system identification sparsity variable forgetting factor zero attractor

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Modification of recursive least squares algorithm for Linear Time-Varying Systems 35

Modification of Recursive Least Squares Algorithm for Linear...

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第35届中国控制会议

作者： ZHANG Wanxin ZHU Jihong Department of Computer Science and Technology Tsinghua University

ISBN: (纸本)9781509009107

Modification of recursive least squares algorithm is presented for identification of linear time-varying systems. The basic idea is to divide the weighting vector into two part. One represents the main variation tendency of the time-varying parameters, while the other is a slowly varying vector. First the former is determined by a procedure based on the dependency of data, and then the remaining part is identified using recursive least squares algorithm with forgetting factor. The modified algorithm avoids the problems appeared in rapidly varying situations, with good tracking ability.

关键词： linear time-varying systems recursive least squares algorithm forgetting factor correlation coefficients

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M^th Order FIR Filtering for EEG denoising using Adaptive recursive least squares algorithm 7

<i>M<SUP>th</SUP></i> Order FIR Filtering for EEG denoising ...

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7th International Conference on Computational Intelligence and Communication Networks (CICN)

作者： Roy, Vandana Shukla, Shailja GGITS Jabalpur 482005 MP India JEC Jabalpur 482011 MP India

ISBN: (纸本)9781509000760

in EEC;Electroencephalogram signals Artifacts records are originated due to various factors as line interference, EOG (electro-Oculogram) and ECG (electrocardiogram). These noise sources upsurge the striving in analyzing the EEG and to procurement clinical information. Therefore, specific filters design is obligatory to diminution of such artifacts in EEG records. This research work anticipated an adaptive filtering method for eradicating ocular artifacts from EEG records by performing. M-th Order FIR Filtering on Adaptive RLS algorithm. In this paper, the method accuracy is estimated by utilizing virtual data quantitatively and equated with the precision of the time-domain regression method. The outcomes suggest that EEG channels are frequency dependent for transfer of ocular signal. The proposed adaptive filtering technique is more precise for denoising of EEG signals.

关键词： Adaptive filtering FIR filters recursive least squares algorithm artifacts ocular signal EEG signals

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Identification of Building Envelope Overall Coefficient of Heat Transfer using recursive least squares algorithm

Identification of Building Envelope Overall Coefficient of H...

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1st International Conference on Civil Engineering, Architecture and Building Materials (CEABM 2011)

作者： Yu, Guoqing Gao, Gangfeng Lin, Xinfeng Shanghai Univ Sci & Technol Sch Environm & Architecture Shanghai 200093 Peoples R China Shanghai KST Energy Conservat Technol Co Ltd Shanghai 201108 Peoples R China

ISBN: (纸本)9783037851272

This paper introduces the methodology and procedures of identification of overall coefficient of heat transfer (U-factor) of building envelopes using recursive least squares algorithm and dynamic heat transfer data. Application this method to three types of typical to examine the correctness and feasibility of this method. The following conclusions can be obtained: 1) Identification of U-factor of building envelopes using recursive least squares algorithm is feasible for engineering purpose, the identified U-factor can be near to its real value;2)The testing periods can be much shorter than the steady testing;3)The identification error is associated with the thermal inertia. The error is larger as the thermal inertia of building envelope is large within the same testing circumstances.

关键词： Identification recursive least squares algorithm Overall Coefficient of Heat Transfer Building Envelope

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Online Identification of Induction Machine Parameter Deviations for Aging Detection - A Comparative Study Using recursive least squares algorithm and Extended Kalman Filter

Online Identification of Induction Machine Parameter Deviati...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Nachtsheim, Martin Grund, Karina Endisch, Christian Kennel, Ralph Tech Hsch Ingolstadt Inst Innovat Mobil Ingolstadt Germany Tech Univ Munich Sch Engn & Design Dept Energy & Proc Engn Munich Germany

ISBN: (纸本)9798350397420

The use of electrical machines in automotive traction systems is rapidly increasing. To ensure operational safety, the machine behavior is monitored to detect failures or aging effects. Besides other approaches, online parameter identification is suited for real-time observation of the machine condition during operation. Two of the most established online parameter identification algorithms are the recursive least squares and the extended Kalman filter algorithm. In existing approaches the algorithms identify the absolute parameter values. In this paper the used identification models are modified to directly identify the parameter deviation related to the reference values. This results in an additional advantage in identifying operational parameter changes because nonlinear behavior is provided by the respective parameter reference. The performance of the proposed algorithms to monitor different electrical parameter changes is compared using an extended analytical induction machine model.

关键词： Induction Machine Online Parameter Identification Extended Kalman Filter recursive least squares algorithm Aging Detection

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Processing of Fetal Heart Rate through Non-invasive Adaptive System Based on recursive least squares algorithm 14

Processing of Fetal Heart Rate through Non-invasive Adaptive...

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Conference on Optical Materials and Biomaterials in Security and Defence Systems Technology XIV

作者： Fajkus, Marcel Nedoma, Jan Martinek, Radek Vasinek, Vladimir Tech Univ Ostrava VSB Fac Elect Engn & Comp Sci Dept Telecommun Ostrava Czech Republic Tech Univ Ostrava VSB Fac Elect Engn & Comp Sci Dept Cybernet & Biomed Engn Ostrava Czech Republic

ISBN: (纸本)9781510613454;9781510613447

In this article, we describe an innovative non-invasive method of Fetal Phonocardiography (fPCG) using fiber-optic sensors and adaptive algorithm for the measurement of fetal heart rate (fHR). Conventional PCG is based on a noninvasive scanning of acoustic signals by means of a microphone placed on the thorax. As for fPCG, the microphone is placed on the maternal abdomen. Our solution is based on patent pending non-invasive scanning of acoustic signals by means of a fiber-optic interferometer. Fiber-optic sensors are resistant to technical artifacts such as electromagnetic interferences (EMI), thus they can be used in situations where it is impossible to use conventional EFM methods, e.g. during Magnetic Resonance Imaging (MRI) examination or in case of delivery in water. The adaptive evaluation system is based on recursive least squares (RLS) algorithm. Based on real measurements provided on five volunteers with their written consent, we created a simplified dynamic signal model of a distribution of heartbeat sounds (HS) through the human body. Our created model allows us to verification of the proposed adaptive system RLS algorithm. The functionality of the proposed non-invasive adaptive system was verified by objective parameters such as Sensitivity (S+) and Signal to Noise Ratio (SNR).

关键词： fetal heart rate adaptive algorithm recursive least squares algorithm

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