@inproceedings{Zaidi-IFAC-2014,
  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-$\alpha$) 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.},
  address = {Cape Town, South Africa},
  author = {Zaidi, Salman and Kroll, Andreas},
  booktitle = {19th IFAC World Congress},
  doi = {doi:10.3182/20140824-6-ZA-1003.01443},
  interhash = {5950b2dbce1ee617a4c41b0e1bdbe3d9},
  intrahash = {7a1641f201b6e94042940daed2f19f87},
  language = {english},
  month = {24-29. August},
  mrtnote = {peer,FuzzyT2},
  pages = {3226-3231},
  title = {On Identifying Envelop Type Nonlinear Output Error Takagi-Sugeno Fuzzy Models for Dynamic Systems with Uncertainties},
  year = 2014
}