engleski

Flexible Lyapunov Function based Model Predictive Direct Current Control of Permanent Magnet Synchronous Generator

In this paper a dual-mode model predictive direct current control (MP-DCC) algorithm for a permanent magnet synchronous generator (PMSG), which minimizes switching losses in a two-level synchronous generator side converter (SGSC), is proposed. The proposed algorithm consists of two different modes, namely tracking mode where the control objective is to steer the stator currents to a control invariant set where the stator currents are ultimately bounded and a minimization of switching losses mode once inside of this set. The size of the control invariant set can be arbitrarily chosen within bounds defined with PMSG and SGSC parameters, therefore switching losses can be more or less penalized in the steady state. In order to guarantee the recursive feasibility and stability of the proposed algorithm, a flexible control Lyapunov function (CLF) is employed as an optimization problem constraint. Since a flexible CLF is a non-monotonically decreasing function, it complies with cost function which penalizes switching losses thus enables penalizing switching losses even in transient state opposing to the standard monotonically decreasing CLF. Simulation results show that by using proposed control algorithm stator current tracking and minimization of switching losses both in transient and steady state are achieved while the recursive feasibility and stability are guaranteed regardless of the cost function. By adjusting weighting matrices of the optimization problem, desired trade-off between low stator current ripple and minimization of switching losses can be achieved.

Model Predictive Control ; Direct Current Control ; Permanent Magnet Synchronous Generator

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