Flexible Lyapunov function based model predictive direct current control of permanent magnet synchronous generator

Abstract

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 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 they are ultimately bounded and a minimization of switching losses mode once inside 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 recursive feasibility and stability of the proposed algorithm, regardless of a cost function, a flexible control Lyapunov function (CLF) is employed as an optimization problem constraint which enables penalizing switching losses even in the transient state. In that way a desired trade-off between low stator current ripple and a minimization of switching losses can be achieved by properly choosing the objective function for the corresponding optimization problem.