| 1. |
- Decuyper, J., et al.
(författare)
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A nonlinear model of vortex-induced forces on an oscillating cylinder in a fluid flow
- 2020
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Ingår i: Journal of Fluids and Structures. - : ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD. - 0889-9746 .- 1095-8622. ; 96
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Tidskriftsartikel (refereegranskat)abstract
- A nonlinear model relating the imposed motion of a circular cylinder, submerged in a fluid flow, to the transverse force coefficient is presented. The nonlinear fluid system, featuring vortex shedding patterns, limit cycle oscillations and synchronisation, is studied both for swept sine and multisine excitation. A nonparametric nonlinear distortion analysis (FAST) is used to distinguish odd from even nonlinear behaviour. The information which is obtained from the nonlinear analysis is explicitly used in constructing a nonlinear model of the polynomial nonlinear state-space (PNLSS) type. The latter results in a reduction of the number of parameters and an increased accuracy compared to the generic modelling approach where typically no such information of the nonlinearity is used. The obtained model is able to accurately simulate time series of the transverse force coefficient over a wide range of the frequency-amplitude plane of imposed cylinder motion. (C) 2020 Elsevier Ltd. All rights reserved.
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| 2. |
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| 3. |
- Decuyper, J., et al.
(författare)
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Retrieving highly structured models starting from black-box nonlinear state-space models using polynomial decoupling
- 2021
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Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 146
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Tidskriftsartikel (refereegranskat)abstract
- Nonlinear state-space modelling is a very powerful black-box modelling approach. However powerful, the resulting models tend to be complex, described by a large number of parameters. In many cases interpretability is preferred over complexity, making too complex models unfit or undesired. In this work, the complexity of such models is reduced by retrieving a more structured, parsimonious model from the data, without exploiting physical knowledge. Essential to the method is a translation of all multivariate nonlinear functions, typically found in nonlinear state-space models, into sets of univariate nonlinear functions. The latter is computed from a tensor decomposition. It is shown that typically an excess of degrees of freedom are used in the description of the nonlinear system whereas reduced representations can be found. The method yields highly structured state-space models where the nonlinearity is contained in as little as a single univariate function, with limited loss of performance. Results are illustrated on simulations and experiments for: the forced Duffing oscillator, the forced Van der Pol oscillator, a Bouc-Wen hysteretic system, and a Li-Ion battery model. (C) 2020 Elsevier Ltd. All rights reserved.
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| 4. |
- Marconato, A., et al.
(författare)
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Identification of the Silverbox Benchmark Using Nonlinear State-Space Models
- 2012
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Ingår i: IFAC Proceedings Volumes (IFAC-PapersOnline). - 2405-8963. - 9783902823069 ; 16:1, s. 632-637
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Konferensbidrag (refereegranskat)abstract
- This work presents the application of an initialization scheme for nonlinear state-space models on a real data benchmark example: the Silverbox problem. The goal of the proposed approach is to transform the identification of a nonlinear dynamic system into an approximate static problem, so that system dynamics and nonlinear terms are identified separately. Classic identification techniques are used to handle dynamics, while regression methods from the statistical learning community are introduced to estimate the nonlinearities in the model. Results obtained on the Silverbox problem are discussed and compared with the performance of other related methods.
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| 5. |
- Marconato, A., et al.
(författare)
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Improved Initialization for Nonlinear State-Space Modeling
- 2014
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Ingår i: IEEE Transactions on Instrumentation and Measurement. - 1557-9662 .- 0018-9456. ; 63:4, s. 972-980
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Tidskriftsartikel (refereegranskat)abstract
- This paper discusses a novel initialization algorithmfor the estimation of nonlinear state-space models. Good initialvalues for the model parameters are obtained by identifyingseparately the linear dynamics and the nonlinear terms inthe model. In particular, the nonlinear dynamic problem istransformed into an approximate static formulation, and simpleregression methods are applied to obtain the solution in a fast andefficient way. The proposed method is validated by means of twomeasurement examples: the Wiener-Hammerstein benchmarkproblem, and the identification of a crystal detector.
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| 6. |
- Marconato, A., et al.
(författare)
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Separate initialization of dynamics and nonlinearities in nonlinear state-space models
- 2012
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Ingår i: 2012 IEEE I2MTC - International Instrumentation and Measurement Technology Conference, Proceedings. - 9781457717710 ; , s. 2104-2108
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Konferensbidrag (refereegranskat)abstract
- This work focuses on the identification of nonlinear dynamic systems. In particular the problem of obtaining good starting values for the identification of nonlinear state-space models is addressed. A fast and efficient initialization algorithm is proposed, combining the use of methods from the statistical learning community to model the nonlinearities and classic system identification tools to capture system dynamics. The performance of the method is evaluated on simulation examples.
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| 7. |
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| 8. |
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| 9. |
- Marconato, A., et al.
(författare)
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Initialization of nonlinear state-space models applied to the Wiener–Hammerstein benchmark
- 2012
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Ingår i: Control Engineering Practice. - : Elsevier BV. - 0967-0661. ; 20:11, s. 1126-1132
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Tidskriftsartikel (refereegranskat)abstract
- In this work a new initialization scheme for nonlinear state-space models is applied to the problem of identifying a Wiener–Hammerstein system on the basis of a set of real data. The proposed approach combines ideas from the statistical learning community with classic system identification methods. The results on the benchmark data are discussed and compared to the ones obtained by other related methods.
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| 10. |
- Sanchez, B., et al.
(författare)
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On the calculation of the D-optimal multisine excitation power spectrum for broadband impedance spectroscopy measurements
- 2012
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Ingår i: Measurement science and technology. - : IOP Publishing. - 0957-0233 .- 1361-6501. ; 23:8, s. 085702-
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Tidskriftsartikel (refereegranskat)abstract
- The successful application of impedance spectroscopy in daily practice requires accurate measurements for modeling complex physiological or electrochemical phenomena in a single frequency or several frequencies at different (or simultaneous) time instants. Nowadays, two approaches are possible for frequency domain impedance spectroscopy measurements: (1) using the classical technique of frequency sweep and (2) using (non-)periodic broadband signals, i.e. multisine excitations. Both techniques share the common problem of how to design the experimental conditions, e.g. the excitation power spectrum, in order to achieve accuracy of maximum impedance model parameters from the impedance data modeling process. The original contribution of this paper is the calculation and design of the D-optimal multisine excitation power spectrum for measuring impedance systems modeled as 2R-1C equivalent electrical circuits. The extension of the results presented for more complex impedance models is also discussed. The influence of the multisine power spectrum on the accuracy of the impedance model parameters is analyzed based on the Fisher information matrix. Furthermore, the optimal measuring frequency range is given based on the properties of the covariance matrix. Finally, simulations and experimental results are provided to validate the theoretical aspects presented.
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