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A study of an inverse method for the estimation of impulsive heat flux

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2000年第6期337卷 661-671页

作者： Lee, WS Ko, YH Ji, CC Chung Cheng Inst Technol Dept Appl Chem Taoyuan 33509 Taiwan

The adaptive input estimation approach which is based on the Kalman filter technique combined with a variable forgetting factor as a weighting function in recursive least-squares algorithm is adopted to investigate the estimation of impulsive heat flux of inverse heat conduction problem from experimental data. Four specific charge designs for igniters with impulsive heat flux input are solved to illustrate the effectiveness and good accuracy of the presented method. (C) 2000 The Franklin Institute. Published by Elsevier Science Ltd. All rights reserved.

关键词： Kalman filter heat aux recursive least-squares algorithm inverse heat conduction

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A clustering-based method for fuzzy modeling

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 1999年第6期E82D卷 1058-1065页

作者： Wong, CC Chen, CC Tamkang Univ Dept Elect Engn Taipei Hsien Taiwan

In this paper, a clustering-based method is proposed for automatically constructing a multi-input Takagi-Sugeno (TS) fuzzy model where only the input-output data of the identified system are available. The TS fuzzy model is automatically generated LS the process of structure identification and parameter identification. In the structure identification step, a clustering method is proposed to provide a systematic procedure to partition the input space so that the number of Fuzzy rules and the shapes of fuzzy sets in the premise part are determined from the given input-output data. In the parameter identification step, the recursive least-squares algorithm is applied to choose the parameter values in the consequent part from the given input-output data. Finally, two examples are used to illustrate the effectiveness of the proposed method.

关键词： fuzzy modeling data clustering recursive least-squares algorithm

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Adaptive filter bank reconstruction using fast multichannel RLS algorithms

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ELECTRONICS LETTERS 1998年第12期34卷 1213-1214页

作者： Chang, DC Wu, WR Natl Chiao Tung Univ Dept Commun Engn Hsinchu 30050 Taiwan

The recursive least-squares (RLS) algorithm has been used in the adaptive synthesis filter bank for fast convergence. However, because of interpolation operations involved in the synthesis process, fast RLS algorithms cannot be applied. In this Letter, an approach is proposed that can formulate subband reconstruction as a multichannel filtering problem. This formulation allows the application of fast multichannel RLS algorithms and substantial reduction in computational complexity.

关键词： least squares approximations fast convergence subband signal reconstruction computational complexity reduction adaptive filter bank reconstruction interpolation operations signal reconstruction recursive least-squares algorithm fast multichannel RLS algorithms synthesis process filtering theory interpolation adaptive synthesis filter bank adaptive filters multichannel filtering problem

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Noise removal from duplicate paleoceanographic time-series: The use of adaptive filtering techniques

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MATHEMATICAL GEOLOGY 1998年第5期30卷 557-574页

作者： Trauth, MH Univ Kiel Inst Geol Palaontol D-24098 Kiel Germany

This study demonstrates that adaptive filters can be used successfully to remove noise from duplicate paleoceanographic time-series. Conventional methods for noise canceling such as fixed filters cannot be applied to paleoceanographic time-series if optimal filtering is to be achieved, because the signal-to-noise ratio is unknown and varies with time. In contrast, an adaptive filter automatically extracts information without any prior initialization of the filter parameters. Two basic adaptive filtering methods, the gradient-based stochastic least-mean-squares (LMS) algorithm and the recursive least-squares (RLS) algorithm have been modified for paleoceanographic applications. The RLS algorithm can he used for noise removal from duplicate records corrupted by stationary noise, for example, carbonate measurements, species counts, or density data. The RLS filter performance is characterized by high accuracy and fast rate of convergence. The modified LMS algorithm out-performs the RLS procedure in a nonstationary environment (e.g., stable isotope records) but at the price of a slower rate of convergence and a reduced accuracy in the final estimate. The application of both algorithms is demonstrated by means of carbonate and stable isotope data.

关键词： least-mean-squares algorithm recursive least-squares algorithm signal-to-noise ratio inverse modeling

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Higher order cumulants-based least squares for nonminimum-phase systems identification

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 1997年第5期44卷 707-716页

作者： Chow, TWS Fei, G Cho, SY Laboratory of Chromatography DEPg.Fac.Quimica Universidad Nacional Autonoma de Mexico Circuito interior Cd Universitaria/CP 04510 Mexico D.F.Mexico

A third-order cumulants-based adaptive recursive least-squares (CRLS) algorithm for the identification of time-invariant nonminimum phase systems, as well as time-variant nonminimum phase systems, has been successfully developed, As higher order cumulants preserve both the magnitude and the phase information of received signals, they have been considered as powerful signal processing tools for nonminimum phase systems, In this paper, the development of the CRLS algorithm is described and examined, A cost function based on the third-order cumulant and the third-order cross cumulant is defined for the development of the CRLS system identification algorithm, The CRLS algorithm is then applied to different moving average (MA) and autoregressive moving average (ARMA) models, In the case of identifying the parameters of an MA model, a direct application of the CRLS algorithm is adequate, When dealing with an ARMA model, the poles and the zeros are estimated separately, In estimating the zeros of the ARMA model, the construction of a residual time-series sequence for the MA part is required, Simulation results indicate that the CRLS algorithm is capable of identifying nonminimum phase and time-varying systems, In addition, because of the third-order cumulant properties, the CRLS algorithm can suppress Gaussian noise and is capable of providing an unbiased estimate in a noisy environment.

关键词： autoregressive moving average model moving average model nonminimum-phase system identification recursive least-squares algorithm third-order cumulants

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REAL-TIME IMPLEMENTATION OF A MIMO ADAPTIVE POWER-SYSTEM STABILIZER

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IEE PROCEEDINGS-C GENERATION TRANSMISSION AND DISTRIBUTION 1990年第3期137卷 186-194页

作者： PAHALAWATHA, NC HOPE, GS MALIK, OP WONG, K Department of Electrical Engineering University of Calgary Calgary Canada

Power systems are non-linear and they are often subjected to random disturbances. Therefore stochastic controllers with on-line system identification are ideally suited to power system control problems. Experience with a real time implementation of an adaptive power system stabiliser to damp the dynamic oscillations of a power system is presented. A multi-input multi-output (MIMO) pole shifting control algorithm together with a least-square system identification is used. The system identification is improved using a variable forgetting factor in the recursive least-squares algorithm. The computation time was greatly reduced by streamlining the identification algorithm using the sparse nature of the matrices associated with the computation and by using parallel processing techniques. The controller was tested in real time using a physical model of a power system. The results show that the damping of the power system dynamic oscillations can be improved by using this controller.

关键词： random disturbances Power engineering computing dynamic oscillations parallel processing parallel processing techniques recursive least-squares algorithm power system computer control Control of electric power systems Self-adjusting control systems MIMO adaptive power system stabiliser online system identification Power system management, operation and economics stability variable forgetting factor Control engineering computing damping pole shifting control algorithm stochastic controllers real-time multi-input multi-output Stability in control theory adaptive control

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PERFORMANCE OF A NEW ADAPTIVE DIVERSITY-EQUALIZATION FOR DIGITAL MOBILE RADIO

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ELECTRONICS LETTERS 1990年第10期26卷 626-627页

作者： SUZUKI, H NTT Radio Commun. Syst. Lab. Take Yokosuka-Shi Japan

A new adaptive diversity-equalisation suitable for mobile radio signal transmission in the mobile radio fast fading environment is proposed. Adaptivity of the diversity-equalisation is enhanced by employing the recursive least-squares algorithm (RLS) with exponential weighting and two newly proposed techniques: bi-directional equalisation (BDE) and transmitter time-diversity (TDD). Computer simulation shows that QPSK transmission performance equivalent to that of four-branch diversity can be obtained with small impairment.

关键词： BER performance QPSK transmission performance RLS adaptive diversity-equalisation adaptive systems bi-directional equalisation bit error rate computer simulation digital mobile radio digital radio systems diversity reception equalisers error statistics exponential weighting fading fast fading environment mobile radio systems phase shift keying radio reception radio signal transmission radiocommunication radiowave propagation reception recursive least-squares algorithm transmitter time-diversity

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MULTIVARIABLE ADAPTIVE CONTROLLER FOR A TURBOGENERATOR

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IEE PROCEEDINGS-D CONTROL THEORY AND APPLICATIONS 1986年第2期133卷 83-89页

作者： SHARAF, SMZ HOGG, BW ABDALLA, OH ELSAYED, ML HELWAN UNIV GARDEN CITYEGYPT

The paper describes the design and application of an adaptive controller which overcomes the nonlinearity of the turbogenerator system. The controller tracks the operating conditions and updates an optimal controller as conditions change. Modelling of the turbogenerator employs an output prediction equation and recursive least-squares algorithm. The design uses identified input/output models, obtained over a range of operating conditions in thePQ-plane. Optimal controllers are designed offline for each zone of thePQ-plane and stored in online memory as a look-up table. The computer monitors the operating conditions of the generator and selects the corresponding optimal controller. The paper presents a practical comparison between the fixed-gain and the look-up-table controllers over a wide range of operating conditions, with various fault conditions, including transient stability boundaries of each controller. The results show that a very high quality of control may be achieved using this adaptive controller.

关键词： turbogenerator a.c. machines Power engineering computing multivariable control systems Multivariable control systems output prediction equation transient stability boundaries recursive least-squares algorithm fixed-gain Control of electric power systems Self-adjusting control systems Optimal control control system synthesis turbogenerators look-up-table controllers adaptive controller optimal control Control engineering computing optimal controller computerised control Control system analysis and synthesis methods multivariable controller adaptive control

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recursive least-squares algorithm REVISITED

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IEE PROCEEDINGS-D CONTROL THEORY AND APPLICATIONS 1981年第2期128卷 74-76页

作者： FUCHS, JJJ Laboratoire d'Automatique Institut de Recherche en Informatique et Systèmes Aléatoires Rennes France

A modified form of the recursive least-squares algorithm is proposed. It is shown that this algorithm possesses interesting properties that are valid without any restriction on experimental conditions, or stability as... 详细信息

关键词： Self-adjusting control systems Simulation, modelling and identification least squares approximations recursive least-squares algorithm Interpolation and function approximation (numerical analysis) parameter estimation adaptive control

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