A comparative study of the use of block-oriented and autoregressive with exogenous inputs (ARX) models in the context of robust controller synthesis is presented in this paper. Parameters uncertainties of the identified models are taken into account in the synthesis of the controllers by state feedback, which aim to assure the maximum attenuation of H2 and H∞ costs. The study consists in evaluating the effects of the variation in the models order and respective estimated deviation in their parameters in the synthesis of robust controllers. The models were obtained from an air heating system with nonlinear dynamics and controllers were designed by means of convex optimization procedures in the form of linear matrix inequalities. The results obtained point to the preferential use of low order Wiener or Hammerstein models, even if they have RMSE and correlation coefficient between simulation error and simulated output indexes worse than higher order models.
system identification, Hammerstein model, Wiener model, block-oriented models, robust control, linear matrix inequalities
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