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              <p>Electrical Throttle Bodies (ETBs) are massively used in the automotive industry and their modeling and control are challenging because of their high nonlinearity and stochasticity. In this paper, we present a data-driven method grounded on the Koopman operator for the identification of a real ETB valve. The model obtained is control-oriented and represented in a quasi- linear-parameter varying framework. Different experiments are performed to evaluate the performance of the proposed method, including the comparison with two classical nonlinear system identification methods.</p>
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