On-line parameter and delay estimation of continuous-time dynamic systems

Kozłowski, Janusz; Kowalczuk, Zdzisław

doi:10.1515/amcs-2015-0017

Cited by 13 publications

(8 citation statements)

References 24 publications

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“…Then, applying the matrix inversion lemma to (33), we obtain a recursive form of the LA algorithm, similar to ( 25)- (27). This means that our LA procedure takes the typical form where the regression (column) vector 𝝋(k) is replaced by 𝝋(k)∕|ê(k)|.…”

Section: La Estimatorsmentioning

confidence: 99%

Iterative‐recursive estimation of parameters of regression models with resistance to outliers on practical examples

Kozłowski,

Kowalczuk

2024

IET Control Theory & Appl

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Here, identification of processes and systems in the sense of the least sum of absolute values is taken into consideration. The respective absolute value estimators are recognised as exceptionally insensitive to large measurement faults or other defects in the processed data, whereas the classical least squares procedure appears to be completely impractical for processing the data contaminated with such parasitic distortions. Since the absolute value quality index cannot be minimised analytically, an iterative solution is used to find optimal estimates of the parameters of the underlying regression model. In addition, an approximate recursive estimator is proposed and implemented for on‐line evaluation of system parameters. The convergence (basic property) of the iterative estimator is show to be proven and some aspects related to the absolute value criterion are explained. This allows for the formulation of practical conclusions and indication of directions for further research. In addition, the effectiveness of the described iterative‐recursive estimation procedures is practically verified by appropriate numerical experiments.

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Section: La Estimatorsmentioning

confidence: 99%

Iterative‐recursive estimation of parameters of regression models with resistance to outliers on practical examples

Kozłowski,

Kowalczuk

2024

IET Control Theory & Appl

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“…Rao and Sivakumar (1979), suggested a method of identifying the system delay by minimizing a cost function whose value depends on the difference between the process and model outputs. An interesting method of identifying both the linear system parameters and delay was proposed by Kozłowski and Kowalczuk (2015). The algorithm presented by Balestrino et al (2000b) can be used for a certain class of systems in the case of single and multiple delays between inputs and outputs and involves introducing additional time-shifted…”

Section: Identification Of the Miso System With Delaysmentioning

confidence: 99%

An Adaptive Identification Method Based on the Modulating Functions Technique and Exact State Observers for Modeling and Simulation of a Nonlinear Miso Glass Melting Process

Byrski

Drapała

Byrski

2019

International Journal of Applied Mathematics and Computer Science

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The paper presents new concepts of the identification method based on modulating functions and exact state observers with its application for identification of a real continuous-time industrial process. The method enables transformation of a system of differential equations into an algebraic one with the same parameters. Then, these parameters can be estimated using the least-squares approach. The main problem is the nonlinearity of the MISO process and its noticeable transport delays. It requires specific modifications to be introduced into the basic identification algorithm. The main goal of the method is to obtain on-line a temporary linear model of the process around the selected operating point, because fast methods for tuning PID controller parameters for such a model are well known. Hence, a special adaptive identification approach with a moving window is proposed, which involves using on-line registered input and output process data. An optimal identification method for a MISO model assuming decomposition to many inner SISO systems is presented. Additionally, a special version of the modulating functions method, in which both model parameters and unknown delays are identified, is tested on real data sets collected from a glass melting installation.

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“…Besides, it is an integral element of dynamic models of physical, chemical, biological, technical and economic systems [1]. However, TDE applications in radio engineering, hydroacoustics, seismology and, especially, in non-destructive testing [1,2] are in the scope of this paper.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of Basic Time Domain Time-Delay Estimators for Locating Leaks in Pipelines

Faerman¹,

Avramchuk²

2020

IJNDC

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The article is devoted to a survey of the known basic Time-Delay Estimation (TDE) methods in the application for detecting fluid leaks in pipeline transport and distribution systems. In the paper, both active and passive estimation methods are considered with respect to the presented generalized classification. However, the main attention is paid to the study of passive methods and their algorithmic implementation. Among the passive methods the Absolute Difference Function (ADF) minimizing algorithms, the Basic Cross-Correlation (BCC) algorithm, the adaptive Least Mean Square (LMS) filtering algorithm are implemented, investigated and compared using a mathematical model of a leak noise signal. All the algorithms are described and the results of the comparison are provided. The advantage of the LMS algorithm in processing the noisy signals is shown. However, its implementation requires choosing a convergence parameter. The necessity in choice of the additional parameter makes the LMS algorithm less practically applicable than the BCC algorithm. The ADF algorithm showed the lowest noise resistivity and can be considered as useful for signal detection, but not for TDE. Some conclusions regarding algorithms' use for solving the problem of locating leaks are stated. In particular, correlation-based TDE algorithms, as generalized cross-correlation and time-frequency cross-correlation, appear to be the best choice for the implementation of leak detection software.

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On-line parameter and delay estimation of continuous-time dynamic systems

Cited by 13 publications

References 24 publications

Iterative‐recursive estimation of parameters of regression models with resistance to outliers on practical examples

Iterative‐recursive estimation of parameters of regression models with resistance to outliers on practical examples

An Adaptive Identification Method Based on the Modulating Functions Technique and Exact State Observers for Modeling and Simulation of a Nonlinear Miso Glass Melting Process

Comparative Study of Basic Time Domain Time-Delay Estimators for Locating Leaks in Pipelines

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