A novel online adaptive time delay identification technique

Bayrak, Alper; Tatlıcıoğlu, Enver

doi:10.1080/00207721.2014.941958

Cited by 11 publications

(5 citation statements)

References 29 publications

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“…denotes the condition number in the l 2 norm, the matrix R k is not ill-conditioned even though the matrix Φ T Λ k Φ Λ k is highly ill-conditioned. Thus the solution for ( 17) is more efficient and numerically stable than the LS solution in (13). Remark 5.…”

Section: The Householder Transformation-based Orthogonal Least Square...mentioning

confidence: 94%

“…The above researches all assumed that there is no time-delay in the processes. However, time-delay is also an important part of many processes in signal processing, communication and control applications [12,13].…”

Section: Introductionmentioning

confidence: 99%

“…For example, Chen et al developed a recursive identification algorithm based on the parallel Kalman filtering and Bayes' estimation [16]. Bayrak et al proposed an online adaptive time-delay identification algorithm based on an adaptive updating law through a minimum-maximum strategy [13]. The above studies require that the system matrices or parameters are known.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Joint parameter and time-delay estimation for a class of Wiener models based on a new orthogonal least squares algorithm

Liu

Zhu

et al. 2023

Preprint

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This paper focuses on the identification of multiple inputs Wiener systems with piecewise-linear nonlinearity. The main objective is to jointly estimate the parameters and time-delays by using limited samples when the system orders are unknown. In order to identify the over-parameterized sparse system under the framework of greedy method, a Householder transformation-based greedy orthogonal least squares algorithm is proposed. In this scheme, the active columns of the information matrix are selected one by one according to a new greedy strategy, then the Householder transformation is employed to maintain an upper-triangular structure for the sub-information matrix, the back-substitution method is adopted to avoid the matrix inversion. Thus the problem of ill-conditioning frequently appears in nonlinear models can be eliminated. The Bayesian information criterion is used to choose the optimal sparsity level. Numerical experiments show that this new scheme can achieve almost optimal generalization performance while requiring less observations than the traditional schemes.

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Section: The Householder Transformation-based Orthogonal Least Square...mentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Joint parameter and time-delay estimation for a class of Wiener models based on a new orthogonal least squares algorithm

Liu

Zhu

et al. 2023

Preprint

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“…A significant amount of research has been devoted to designing time-delay identification algorithms (Ahmed et al, 2006;Belkoura and Richard, 2006;Drakunov et al, 2006;Wang et al, 2008;Bjorklund and Ljung, 2009;Tang et al, 2009;Tang and Guan, 2009;Loxton et al, 2010;Ni et al, 2010;Selvanathan and Tangirala, 2010;Bayrak and Tatlicioglu, 2011;Tan and Cham, 2011). Most of the past research on time-delay identification were usually presented for linear or linearized systems and review of the relevant past research highlights the fact that there are no time-delay identification algorithms for general classes of nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

“…Niculescu and Gu also presented a broad overview, that particularly focused on engineering applications and recent progresses of stability and control of time delay systems [2]. A significant amount of research was devoted to designing time delay identification algorithms [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]. Most of the past research on time delay identification were usually presented for linear or linearized systems and review of the relevant past research highlights the fact that there are no time delay identification algorithms for general classes of nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Online time delay identification and control for general classes of nonlinear systems

Bayrak

Tatlıcıoğlu

2013

Transactions of the Institute of Measurement and Control

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Abstract-In this study, online identification of state delays is discussed. First, a novel adaptive time delay identification technique is proposed for general classes of autonomous nonlinear systems subject to state delays. As an extension, this technique is modified to design a tracking controller for general classes of nonlinear systems subject to state delays. The main novelty of this controller is that identification of unknown state delays is ensured while output tracking objective is satisfied. Extensive numerical simulations are presented that demonstrate the efficiency of the time delay identification algorithm and the tracking controller.

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Joint parameter and time-delay estimation for a class of Wiener models based on a new orthogonal least squares algorithm

Liu,

Zhu

et al. 2024

Nonlinear Dyn

View full text Add to dashboard Cite

This paper focuses on the identification of multiple inputs Wiener systems with piecewise-linear nonlinearity. The main objective is to jointly estimate the parameters and time-delays by using limited samples when the system orders are unknown. In order to identify the over-parameterized sparse system under the framework of greedy method, a Householder transformation-based greedy orthogonal least squares algorithm is proposed. In this scheme, the active columns of the information matrix are selected one by one according to a new greedy strategy, then the Householder transformation is employed to maintain an upper-triangular structure for the subinformation matrix, the back-substitution method is adopted to avoid the matrix inversion. Thus the problem of ill-conditioning frequently appears in nonlinear models can be eliminated. The Bayesian information criterion is used to choose the optimal sparsity level. Numerical experiments show that this new scheme can achieve almost optimal generalization performance while requiring less observations than the traditional schemes.

show abstract

A novel online adaptive time delay identification technique

Cited by 11 publications

References 29 publications

Joint parameter and time-delay estimation for a class of Wiener models based on a new orthogonal least squares algorithm

Joint parameter and time-delay estimation for a class of Wiener models based on a new orthogonal least squares algorithm

Online time delay identification and control for general classes of nonlinear systems

Joint parameter and time-delay estimation for a class of Wiener models based on a new orthogonal least squares algorithm

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