Browsing by Author "b4f3f529-e15c-4258-bb7a-1b6b65477ba8"
Now showing items 1-7 of 7
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(Elsevier Ltd, 2018)Takagi–Sugeno fuzzy models are cataloged as universal approximators and have been proven to be a powerful tool for the prediction of systems. However, in certain cases they may fail to inherit the main properties of a ...
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(Elsevier Ltd, 2018)This paper presents novel control strategies using Takagi–Sugeno fuzzy models combined with a parametric uncertainty robust control approach to address both the nonlinearities of a process and the disturbances that act on ...
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(Institute of Electrical and Electronics Engineers Inc., 2018)In this paper, a new prediction interval model based on a joint supervision loss function for capturing the uncertainties associated with the modeled phenomenon is described. This model provides the upper and lower bounds ...
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(Elsevier B.V., 2018)We present a strategy for the on-line estimation of the aerobic reaction phase length for a partial nitrification process with pH and dissolved oxygen closed-loop control. To overcome existing drawbacks associated to partial ...
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(Elsevier Ltd, 2019)Modulated model predictive control (M 2 PC) allows fixed switching frequency operation of power converters, producing lower ripple and lower total harmonic distortion (THD) in the output signals than those obtained using ...
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(Elsevier, 2019)Prediction interval modelling has been proposed in the literature to characterize uncertain phenomena and provide useful information from a decision-making point of view. In most of the reported studies, assumptions about ...
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(MDPI AG, 2019)This paper proposes a low-complexity small signal model for a 3-leg converter connected to a balanced three-phase, three-wire weak grid and synchronised to this grid using a PLL implemented in a synchronous rotating d-q ...
