Model-Free Predictive Current Control of a Voltage Source Inverter
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Fecha
2020-11
Profesor/a Guía
Facultad/escuela
Idioma
en
Título de la revista
ISSN de la revista
Título del volumen
Editor
Institute of Electrical and Electronics Engineers
Nombre de Curso
Licencia CC
Licencia CC
Resumen
Conventional model predictive control (MPC) of power converter has been widely applied to power inverters achieving high performance, fast dynamic response, and accurate transient control of power converter. However, the MPC strategy is highly reliant on the accuracy of the inverter model used for the controlled system. Consequently, a parameter or model mismatch between the plant and the controller leads to a sub-optimal performance of MPC. In this paper, a new strategy called model-free predictive control (MF-PC) is proposed to improve such problems. The presented approach is based on a recursive least squares algorithm to identify the parameters of an auto-regressive with exogenous input (ARX) model. The proposed method provides an accurate prediction of the controlled variables without requiring detailed knowledge of the physical system. This new approach and is realized by employing a novel state space identification algorithm into the predictive control structure. The performance of the proposed model-free predictive control method is compared with conventional MPC. The simulation and experimental results show that the proposed method is totally robust against parameters and model changes compared with the conventional model based solutions.
Notas
Indexación: Scopus.
Palabras clave
Adaptation models, Load modeling, Mathematical model, Model-free predictive control, MPC, Prediction algorithms, Predictive control, Predictive models, robustness; Uncertainty, voltage source converter
Citación
IEEE Access, 2020
DOI
DOI: 10.1109/ACCESS.2020.3039050