Resumen
In this paper, we present a predictive control algorithm that uses a state-space model. Based on classical control theory, an exact discrete-time model of an induction machine with time-varying components is developed improving the accuracy of state prediction. A torque and stator flux magnitude control algorithm evaluates a cost function for each switching state available in a two-level inverter. The voltage vector with the lowest torque and stator flux magnitude errors is selected to be applied in the next sampling interval. A high degree of flexibility is obtained with the proposed control technique due to the online optimization algorithm, where system nonlinearities and restrictions can be included. Experimental results for a 4-kW induction machine are presented to validate the proposed state-space model and control algorithm.
| Idioma original | English |
|---|---|
| Páginas (desde-hasta) | 1916-1924 |
| Número de páginas | 9 |
| Publicación | IEEE Transactions on Industrial Electronics |
| Volumen | 56 |
| N.º | 6 |
| DOI | |
| Estado | Published - 1 jul 2009 |
Huella dactilar
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering
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Predictive torque control of induction machines based on state-space models. / Miranda, Hernán; Cortés, Patricio; Yuz, Juan I.; Rodríguez, José.
En: IEEE Transactions on Industrial Electronics, Vol. 56, N.º 6, 01.07.2009, p. 1916-1924.Resultado de la investigación: Article
TY - JOUR
T1 - Predictive torque control of induction machines based on state-space models
AU - Miranda, Hernán
AU - Cortés, Patricio
AU - Yuz, Juan I.
AU - Rodríguez, José
PY - 2009/7/1
Y1 - 2009/7/1
N2 - In this paper, we present a predictive control algorithm that uses a state-space model. Based on classical control theory, an exact discrete-time model of an induction machine with time-varying components is developed improving the accuracy of state prediction. A torque and stator flux magnitude control algorithm evaluates a cost function for each switching state available in a two-level inverter. The voltage vector with the lowest torque and stator flux magnitude errors is selected to be applied in the next sampling interval. A high degree of flexibility is obtained with the proposed control technique due to the online optimization algorithm, where system nonlinearities and restrictions can be included. Experimental results for a 4-kW induction machine are presented to validate the proposed state-space model and control algorithm.
AB - In this paper, we present a predictive control algorithm that uses a state-space model. Based on classical control theory, an exact discrete-time model of an induction machine with time-varying components is developed improving the accuracy of state prediction. A torque and stator flux magnitude control algorithm evaluates a cost function for each switching state available in a two-level inverter. The voltage vector with the lowest torque and stator flux magnitude errors is selected to be applied in the next sampling interval. A high degree of flexibility is obtained with the proposed control technique due to the online optimization algorithm, where system nonlinearities and restrictions can be included. Experimental results for a 4-kW induction machine are presented to validate the proposed state-space model and control algorithm.
KW - Induction motor drives
KW - Predictive control
KW - State-space methods
UR - http://www.scopus.com/inward/record.url?scp=67649343052&partnerID=8YFLogxK
U2 - 10.1109/TIE.2009.2014904
DO - 10.1109/TIE.2009.2014904
M3 - Article
AN - SCOPUS:67649343052
VL - 56
SP - 1916
EP - 1924
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
SN - 0278-0046
IS - 6
ER -