Model predictive control for induction motor control reconfiguration after inverter faults

MATÍAS A. NACUSSE; MÓNICA ROMERO; HERNAN HAIMOVICH; MARÍA M. SERON; SERGIO JUNCO

Journal Européen des Systèmes Automatisés

Lavoisier

Año: 2012 vol. 46 p. 307 - 321

1269-6935

This work analyzes the use of model predictive control (MPC) for induction motor (IM) control and compares it with the standard form of the direct torque and flux control (DTFC) strategy. These two strategies are fundamentally different in operation since (i) MPC decides the current control action by on-line minimization of a cost function that uses the available inverter output voltages as optimization variables, whereas (ii) DTFC decides the current control action based on a switching table constructed using a simplified model of the IM. Emphasis is given in this work to the reconfiguration of the control action after voltage source inverter faults. We assume that the fault can be suitably detected and isolated and that the inverter can be reconfigured after the specific fault to continue operation, albeit with a reduced set of achievable output vectors. Based on this reduced set of vectors, we propose to reconfigure the induction motor control algorithm by (i) providing the reduced set of inverter vectors as the reconfigured constraint set of optimization variables for MPC or (ii) instructing DTFC to use a reconfigured switching table. Simulation results show that MPC with prediction horizon N = 1 considerably outperforms DTFC at a modest increment of computational cost. Moreover, this increment is less pronounced under fault since the number of optimization variables is reduced.