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Fast ladder-lattice identification architecture with numerically robust tracking of parameters

IFAC Proceedings Volumes 1991年第7期24卷 105-110页

作者： J. Kadlec Institute of Information Theory and Automation Czech Academy of Sciences and Arts Pod vodárenskou věží 4 18208 Praha 8 Czechoslovakia

A Ladder-Lattice identification algorithm with shift-invariant directional (SID) parameter tracking technique is derived for the fast recursive least-squares (FRLS) identification applications. The method employs forgetting with different weights on the (by latest data) modified and the unmodified part of the minimized quadratic form. The technique is implemented on a Ladder-Lattice computing structure with only small increase of complexity in comparison to the standard Ladder-Lattice structures. The parameter tracking rate and the numerical robustness with respect to insufficiently exciting data are considerably improved.

关键词： Identification least-squares estimation adaptive systems parallel processing recursive algorithms

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A recursive Algorithm for Default Risk Adjustment in Interest Rate Swaps

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IFAC Proceedings Volumes 1998年第16期31卷 61-67页

作者： Frank Fehle The University of Texas at Austin

This paper provides empirical evidence on the cross-sectional and timeseries variation for the pricing of contracts that swap fixed-for floating-rate interest payments in eight international markets. Swap spreads defined as the difference between the fixed swap rate and the yield of a risk-free security of equal maturity are analyzed across markets. A framework, which allows to assess the ability of asymmetric default risk to generate observed spreads, is introduced and used to simulate default risk-adjusted swap rates. For typical yield curve and default conditions asymmetric default risk cannot generate positive swap spreads of the magnitude found in the data. These results are unchanged when incorporating expected or realized LIBOR spreads in the analysis.

关键词： Finance Economics Derivative recursive algorithms Numerical Solutions

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Control of pH in a Continuous Stirred Tank Reactor (CSTR)

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IFAC Proceedings Volumes 1993年第2期26卷 115-126页

作者： R. Tyagi E.J. Davison Department of Test Engineering Northern Telecom Canada Ltd. 8200 Dixie Road Brampton Ontario Canada L6V 2M6 Department of Electrical Engineering University of Toronto Toronto Canada M5S 1A4

The pH control problem in a continuous stirred tank reactor is studied from both atheoretical and application point of view. A reaction invariant model for an acid-base system, which is one of the most complete descriptions for the pH control problem, is utilized. The new controller obtained for the pH control problem is based on a linearization technique and requires that some steady-state experilnents be carried out on the process, before a controller implementation can be achieved. The proposed controller has been applied toa 6th order nonlinear simulation model of a pH process for the case of:(i) time-varying input feed pH concentrations and buffer concentrations,(ii) set-point reference input changes for the desired pH output. Based on the results of these simulations, the controller appears to be quite effective;in particular it gives significant improvements in the response compared to existing controllers proposed in the literature

关键词： pH control control nonlinearities deadbeat control discrete nonlinear systems recursive algorithms state feedback time varying systems linearization technique

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recursive Generalized Total Least Squares with Noise Covariance Estimation

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IFAC Proceedings Volumes 2014年第3期47卷 4637-4643页

作者： Stephan Rhode Felix Bleimund Frank Gauterin Institute of Vehicle System Technology Karlsruhe Institute of Technology 76131 Karlsruhe Germany

We propose a recursive generalized total least-squares (RGTLS) estimator that is used in parallel with a noise covariance estimator (NCE) to solve the errors-in-variables problem for multi-input-single-output linear systems with unknown noise covariance matrix. Simulation experiments show that the suggested RGTLS with NCE procedure outperforms the common recursive least squares (RLS) and recursive total instrumental variables (RTIV) estimators when all measured inputs and the measured output are noisy. Moreover, when all measured inputs are noise-free, RGTLS with NCE performs similarly to RLS, which in this special case is the optimal estimator, and again RTIV was inferior compared with the RGTLS and NCE procedure.

关键词： System identification Errors-in-variables models Linear systems recursive algorithms recursive filters Kalman filters Signal processing

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Identification of Conductive Fiber Parameters with Transcutaneous Electrical Nerve Stimulation Signal Using RLS Algorithm

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IFAC-PapersOnLine 2015年第20期48卷 389-394页

作者： Manuel Schimmack Paolo Mercorelli Institute of Product and Process Innovation Leuphana University of Lueneburg Volgershall 1 D-21339 Lueneburg Germany

This paper presents a scaled system identification method for medical application in the fields of noninvasive nerve stimulation and neurological disease treatment. The recursive Least Squares (RLS) method with an implemented forgetting factor was used to estimate parameters, including inductance, within the nano range of a linear model, using input-output scaling factors. To estimate the parameters in the nano range, the input signal must have a very high frequency, which subsequently requires a very high sampling rate, and therefore expensive hardware and precise programming. In contrast, this technique allows for a lower sampling rate and an input signal with low frequency to identify the parameters characterizing the linear model, without requiring additional hardware for the estimation process. This method was used to provide a scaled identification bandwidth together with a reduced sampling rate to use a Transcutaneous Electrical Nerve Stimulation signal (TENS) by themself for the identification process. In addition, the proposed method identified the inductance of the conductive textile system, the most critical parameter to be estimated. The measured results indicated that the proposed RLS method along with a forgetting factor was an effective and robust method for estimating the parameters.

关键词： Transcutaneous Electrical Nerve Stimulation Signal Output-Error (OE) Model Parameter Estimation recursive algorithms recursive Least-squares method Least-Squares identification

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Comparing recursive Estimators in the Presence of Unmodeled Dynamics

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IFAC Proceedings Volumes 2010年第10期43卷 128-133页

作者： Magnus Nilsson Bo Egardt Magnus Nilsson and Bo Egardt are with the Dept. of Signals and Systems Chalmers University of Technology Sweden

Indirect recursive identification algorithms have been suggested for robust control design in the literature. The purpose of this contribution is to clarify that such algorithms need proper calculation of the update direction in undermodeled situations. An indirect pseudolinear regression is compared to a (more suitable) indirect recursive prediction-error method. Their asymptotic properties are examined through simulations, using a specific control structure.

关键词： Adaptive control recursive algorithms Identification algorithms

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Application of a recursive subspace identification algorithm to change detection

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IFAC Proceedings Volumes 2003年第16期36卷 1357-1362页

作者： Hiroshi Oku Osaka Institute of Technology 5-16-1 Omiya Asahi-ku Osaka 535-8585 JAPAN

This paper presents a new change detection method with the aid of subspace identification. The proposed method is based on monitoring a change in variance of a statistic generated by a recursive subspace identification algorithm. An asymptotic property of the statistic is presented. Without changes during sampling, it is shown that, under relevant assumptions. the statistic converges in probability to a stack of noise vectors multiplied from the left side by a Toeplitz matrix. A numerical example illustrates that the proposed method can detect changes in the dynamics of a system, without being disturbed by changes in the dynamics of an input signal which are not our concern.

关键词： system identification subspace methods recursive algorithms instrumental variable methods fault detection statistical analysis multivariable systems

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Fast Moving Window Algorithm for QR and Cholesky Decompositions

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IFAC Proceedings Volumes 2008年第2期41卷 10106-10111页

作者： Wuxing Liang Uwe Kruger Xun Wang Lei Xie Tim Littler School of Electronics Electrical Engineering and Computer Science Queen's University Belfast BT9 5AH U.K. Department of Electrical Engineering The Petroleum Institute P.O. Box 2533 Abu Dhabi U. A. E. Institute of Advanced Process Control Zhejiang University Hangzhou 310027 P.R. China

This paper proposes a fast moving window algorithm for QR and Cholesky decompositions by simultaneously applying data updating and downdating. The developed procedure is based on inner products and entails a similar downdating to that of the Chambers’ approach. For adding and deleting one row of data from the original matrix, a detailed analysis shows that the proposed algorithm outperforms existing ones in terms or computational efficiency, if the number of columns exceeds 7. For a large number of columns, the proposed algorithm is numerically superior compared to the traditional sequential technique.

关键词： Cholesky factorization QR decomposition adaptive algorithms update and downdate recursive algorithms

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Online algorithms for the Construction of Guaranteed Confidence Sets for the Parameters of Time-varying Systems

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IFAC Proceedings Volumes 2009年第10期42卷 426-431页

作者： Kelvin J. Layton Erik Weyer Marco C. Campi Department of Electrical and Electronic Engineering The University of Melbourne Parkville VIC 3010 Australia Department of Electrical Engineering and Automation University of Brescia Via Branze 38 25123 Brescia Italy

The “Leave-out Sign-dominant Correlation Regions” (LSCR) algorithm is extended to deliver a guaranteed confidence set for the parameters of a time-varying system at any given time. The algorithm is derived by assuming that an upper bound on the parameter variation is available, and the delivered confidence set is valid without any prior knowledge of the noise. Simulation examples are provided to illustrate the performance of the algorithm.

关键词： Time-varying systems System identification Parameter estimation recursive algorithms Uncertainty

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Direct Linearization of Weakly Nonlinear Volterra Systems Using Adaptive Linear and Nonlinear FIR Filters

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IFAC Proceedings Volumes 2009年第10期42卷 646-651页

作者： Emad Abd-Elrady Li Gan Christian Doppler Laboratory for Nonlinear Signal Processing Institute of Signal Processing and Speech Communication Graz University of Technology. Inffeldgasse 16b A-8010 Graz Austria

Linearization of nonlinear systems is a very important topic in many practical applications. The linearization scheme of Gao and Snelgrove (1990) for weakly nonlinear Volterra systems using adaptive linear and nonlinear FIR filters is considered in this paper. The coefficients of these filters can be indirectly estimated using the Least Mean Squares (LMS) and recursive Prediction Error Method (RPEM) algorithms as done in Gan and Abd-Elrady (2008b). In this paper, these coefficients are directly estimated using the Nonlinear Filtered-x Least Mean Squares (NFxLMS) algorithm and the Spectral Magnitude Matching (SMM) method. Simulation study shows that the suggested direct approaches can significantly suppress spectral regrowth and reduce nonlinear distortion as well as the indirect approach.

关键词： Adaptive filters Linearization Nonlinear distortion Nonlinear systems Parameter estimation recursive algorithms Volterra series

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