| Author | Title | Year | Journal/Proceedings | DOI/URL | |
|---|---|---|---|---|---|
| Zaidi, S. | System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models | 2018 | Schriftenreihe Mess- und Regelungstechnik der Universität Kassel (9) , pp. 150 , kassel university press , October , Dissertation | URL PhD-11 | |
| Abstract: Some novel approaches to estimate Nonlinear Output Error (NOE) models using TS fuzzy models for a class of nonlinear dynamic systems having variability in their outputs is presented in this dissertation. Instead of using unrealistic assumptions about uncertainty, the most common of which is normality, the proposed methodology tends to capture effects caused by the real uncertainty observed in the data. The methodology requires that the identification method must be repeated offline a number of times under similar conditions. This leads to multiple inputoutput time series from the underlying system. These time series are preprocessed using the techniques of statistics and probability theory to generate the envelopes of response at each time instant. By incorporating interval data in fuzzy modelling and using the theory of symbolic interval-valued data, a TS fuzzy model with interval antecedent and consequent parameters is obtained. The proposed identification algorithm provides for a model for predicting the center-valued response as well as envelopes as the measure of uncertainty in system output. | |||||
BibTeX:
@phdthesis{2018-Zaidi-PhD-TS_Ident,
author = {Salman Zaidi}
, title = {System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models}
, publisher = {kassel university press}
, school = {Schriftenreihe Mess- und Regelungstechnik der Universität Kassel}
, type = {Dissertation}
, year = {2018}
, number = {9}
, pages = {150}
, url = {https://www.upress.uni-kassel.de/katalog/abstract.php?978-3-7376-0650-9}
, isbn = {978-3-7376-0650-9}
, mrtnr = {PhD-11} }
|
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| Zaidi, S. & Kroll, A. | NOE TS Fuzzy Modelling of Nonlinear Dynamic Systems with Uncertainties using Symbolic Interval-valued data | 2017 | Applied Soft Computing , Vol. 57 , pp. 353-362 | DOI URL PDF | |
| Abstract: An approach to Nonlinear Output Error (NOE) modelling using Takagi -- Sugeno (TS) fuzzy model for a class of nonlinear dynamic systems having variability in their outputs is presented. Furthermore, the approach is compared and graphically illustrated with other alternate approaches on the basis of interval data and interval membership functions. Assuming the identification method can be repeated offline a number of times under similar conditions, multiple input -- output time series can be obtained from the underlying system. These time series are pre-processed using the techniques of statistics and probability theory to generate the envelopes of response (curves outlining the upper and lower extremes of response) at each time instant. Two types of envelopes are described in this research: the max -- min envelopes and the envelopes based on the confidence intervals provided by extended Chebyshev's inequality. By incorporating interval data in fuzzy modelling and using the theory of symbolic interval-valued data, a TS fuzzy model with interval antecedent and consequent parameters is obtained. This algorithm provides a model for predicting the expected response as well as envelopes. In order to validate the presented model, a simulation case study is devised in this paper. Moreover, it is demonstrated on the real data obtained from an electro-mechanical throttle valve. | |||||
BibTeX:
@article{Zaidi-ASC-2016,
author = {Salman Zaidi and Andreas Kroll}
, title = {NOE TS Fuzzy Modelling of Nonlinear Dynamic Systems with Uncertainties using Symbolic Interval-valued data}
, journal = {Applied Soft Computing}
, year = {2017}
, volume = {57}
, pages = {353-362}
, url = {http://www.sciencedirect.com/science/article/pii/S1568494617301758}
, doi = {http://dx.doi.org/10.1016/j.asoc.2017.04.004}
}
|
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| Zaidi, S. & Kroll, A. | On Interval-valued-data Type-1 Takagi-Sugeno fuzzy systems for uncertain nonlinear dynamic system identification [BibTeX] |
2016 | at -- Automatisierungstechnik , Vol. 64 (6) , pp. 418 - 427 | URL | |
BibTeX:
@article{Zaidi-AT-2016,
author = {Salman Zaidi and Andreas Kroll}
, title = {On Interval-valued-data Type-1 Takagi-Sugeno fuzzy systems for uncertain nonlinear dynamic system identification}
, journal = {at -- Automatisierungstechnik}
, year = {2016}
, volume = {64}
, number = {6}
, pages = {418 -- 427}
, url = {http://www.degruyter.com/view/j/auto}
}
|
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| Zaidi, S. & Kroll, A. | A Novel Approach to T-S Fuzzy Modeling of Nonlinear Dynamic Systems with Uncertainties using Symbolic Interval-Valued Outputs | 2015 | Proceedings of the 17th IFAC Symposium on System Identification (SysID) , pp. 1196 - 1201 , Beijing, China , October 19-21 | DOI | |
| Abstract: A novel approach to Takagi-Sugeno (T-S) fuzzy modeling of a class of nonlinear dynamic systems having variability in their outputs for the Nonlinear Output Error (NOE) case is addressed in this article. Multiple input-output datasets were obtained by repeating the identification experiment. The variability in the output time series is captured by defining the envelops of response at each time instant. These envelops actually provide the confidence interval based upper and lower bounds of the output time series using the extended Chebyshev's Inequality. Different from the previous approach, in which two independent T-S fuzzy models were used for identifying each bound, a single T-S fuzzy model is identified in this work, which resulted in interval parameters for the antecedent and consequent variables. This is accomplished by first transforming the bounds into the symbolic interval-valued data and then using this data for identification. In order to get the expected response, the estimated lower and upper bound time series of the identified T-S fuzzy model were averaged out at each time instant, as permitted by the structure of the extended Chebyshev's Inequality. The proposed approach is demonstrated and validated for the experimental data obtained from diesel-engine electro-mechanical throttle valve. | |||||
BibTeX:
@inproceedings{Zaidi-SYSID-2015,
author = {Salman Zaidi and Andreas Kroll}
, title = {A Novel Approach to T-S Fuzzy Modeling of Nonlinear Dynamic Systems with Uncertainties using Symbolic Interval-Valued Outputs}
, booktitle = {Proceedings of the 17th IFAC Symposium on System Identification (SysID)}
, year = {2015}
, pages = {1196 -- 1201}
, address = {Beijing, China}
, doi = {http://dx.doi.org/10.1016/j.ifacol.2015.12.294}
}
|
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| Zaidi, S. & Kroll, A. | Electro-Mechanical Throttle as a Benchmark Problem for Nonlinear System Identification with Friction [BibTeX] |
2014 | 24. Workshop Computational Intelligence , pp. 173-186 , KIT Scientific Publishing , Dortmund , 27.-28. November , GMA-FA 5.14 | URL | |
BibTeX:
@inproceedings{Zaidi-GMA-2014,
author = {Salman Zaidi and Andreas Kroll}
, title = {Electro-Mechanical Throttle as a Benchmark Problem for Nonlinear System Identification with Friction}
, booktitle = {24. Workshop Computational Intelligence}
, publisher = {KIT Scientific Publishing}
, year = {2014}
, pages = {173-186}
, address = {Dortmund}
, url = {http://www.rst.e-technik.tu-dortmund.de/cms/de/Veranstaltungen/GMA-Fachausschuss/index.html}
}
|
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| Zaidi, S. & Kroll, A. | On Identifying Envelop Type Nonlinear Output Error Takagi-Sugeno Fuzzy Models for Dynamic Systems with Uncertainties | 2014 | 19th IFAC World Congress , pp. 3226-3231 , Cape Town, South Africa , 24-29. August | DOI | |
| Abstract: In modeling of a stochastic nonlinear dynamic system from input-output data, it may be of interest to model uncertainty in the underlying system besides predicting a most likely or average response of the system. Due to stochasticity in the system behavior, the data obtained for identification can be considered as one realization of the underlying stochastic phenomenon. In order to effectively deal with the identification of such systems, it may be advantageous to repeat the identification experiment multiple times under similar conditions. The multiple input-output time series generated in this way thus contain information about stochastic variations within the system. This paper presents one of the possible approaches to effectively deal with identification in such scenario in the framework of Nonlinear Output Error (NOE) Takagi-Sugeno (TS) fuzzy models. Based on extended Chebyshev's inequality for finite samples, the lower and upper boundaries of the output time-series are obtained using (1-$) confidence interval (envelops of the response). The proposed identification algorithm provides a model for predicting the most likely value as well as the boundary models for predicting the envelops of the output signal. The experimental results for an electro-mechanical throttle shows the applicability and validity of the proposed approach. | |||||
BibTeX:
@inproceedings{Zaidi-IFAC-2014,
author = {Salman Zaidi and Andreas Kroll}
, title = {On Identifying Envelop Type Nonlinear Output Error Takagi-Sugeno Fuzzy Models for Dynamic Systems with Uncertainties}
, booktitle = {19th IFAC World Congress}
, year = {2014}
, pages = {3226-3231}
, address = {Cape Town, South Africa}
, doi = {http://dx.doi.org/10.3182/20140824-6-ZA-1003.01443}
}
|
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| Zaidi, S. & Kroll, A. | On identifying nonlinear envelop type dynamical T-S fuzzy models for systems with uncertainties: method and application to electro-mechanical throttle [BibTeX] |
2013 | 23. Workshop Computational Intelligence , pp. 129-143 , KIT Scientific Publishing , Dortmund , 5-6. Dezember , GMA-FA 5.14 | URL | |
BibTeX:
@inproceedings{Zaidi-GMA-2013,
author = {Salman Zaidi and Andreas Kroll}
, title = {On identifying nonlinear envelop type dynamical T-S fuzzy models for systems with uncertainties: method and application to electro-mechanical throttle}
, booktitle = {23. Workshop Computational Intelligence}
, publisher = {KIT Scientific Publishing}
, year = {2013}
, pages = {129-143}
, address = {Dortmund}
, url = {http://www.rst.e-technik.tu-dortmund.de/cms/de/Veranstaltungen/GMA-Fachausschuss/index.html}
}
|
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| Zaidi, S., Kroll, A. & Sommer, H.-J. | On Description and Identification of Uncertainties in System Modeling with Fuzzy Logic [BibTeX] |
2012 | 22. Workshop Computational Intelligence , pp. 179-199 , KIT Scientific Publishing , Dortmund , 6-7. Dezember , GMA-FA 5.14 | URL | |
BibTeX:
@inproceedings{Zaidi-GMA-2012,
author = {Salman Zaidi and Andreas Kroll and Hanns-Jakob Sommer}
, title = {On Description and Identification of Uncertainties in System Modeling with Fuzzy Logic}
, booktitle = {22. Workshop Computational Intelligence}
, publisher = {KIT Scientific Publishing}
, year = {2012}
, pages = {179-199}
, address = {Dortmund}
, url = {http://www.rst.e-technik.tu-dortmund.de/cms/de/Veranstaltungen/GMA-Fachausschuss/index.html}
}
|
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