METHOD AND CONTROLLER FOR MODEL PREDICTIVE CONTROL OF A POWER CONVERTER

摘要

In order to allow a method for model predictive control of a power converter (1), which method uses sufficiently short sampling steps T_s of the MPC control, but long prediction horizons T_pred, there is provision to describe the power converter (1) to be controlled by using a bilinear differential equation system and to describe the time characteristic of the manipulated variables α over a prediction horizon T_pred by means of ansatz functions h_k(t), in the form (I), with approximation factors β_k. The bilinear differential equation system is discretized over time. A cost function (II) defined over the prediction horizon Tpred is optimized in each sampling step T_s of the model predictive control by defining a Lagrange function L_j, for the cost function J_j and the differential equation system and, in an iteration loop, determining the states (III) over the prediction horizon T_pred and a gradient (IV) of the Lagrange function L_j as search direction in a forward integration in each iteration step z. In each iteration step z the manipulated variable vector (V) for the next iteration step (z+1) is ascertained from the manipulated variable vector (VI) of the current iteration step z, a step size (VII) and the gradient (VIII) in the form (VIIII). The approximation factors (X) of the manipulated variable vector (XI) most recently ascertained in the iteration are used to ascertain the manipulated variables α for the model predictive control in the current sampling step T_s of the model predictive control, and the power converter (1) is controlled using these manipulated variables.