Model Predictive Direct Current Control of a Permanent Magnet Synchronous Generator Based on Flexible Lyapunov Function Considering Converter Dead Time

This paper proposes a dual-mode model predictive direct current control (MP-DCC) of a permanent magnet synchronous generator (PMSG). The proposed algorithm is capable of minimizing switching losses in a two-level synchronous generator side converter (SGSC). A new prediction model that takes the converter dead time into consideration when choosing the optimal switching state is introduced. The proposed prediction model provides a more accurate state prediction, ensuring that the states of the system stay inside the control invariant set in the steady state, even in the case of a significant converter dead time. To guarantee recursive feasibility and closed-loop stability, a flexible control Lyapunov function (CLF) is employed as an optimization problem constraint, which enables the minimization of switching losses both during transients and in the steady state. The influence of the converter dead time on the performance of the proposed algorithm is considered, and accordingly, a control invariant set is determined. Simulation results show that stator currents are kept within the control invariant set if dead time is taken into account in the prediction model. Furthermore, the proposed algorithm is implemented in a digital control system and experimentally verified on a 375 kW interior PMSG. Experimental results verify that the proposed control algorithm provides a successful flying start of the PMSG and show that the application of the flexible CLF results in a lower switching frequency, but also in higher current ripple. By adjusting the upper bound of the control invariant set, a desired tradeoff between the low stator current ripple and the minimization of switching losses can be achieved.