Data-Driven Nonlinear System Identification of a Throttle Valve Using Koopman Representation
Abstract
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.
| Origin | Files produced by the author(s) |
|---|