One of the main problems of multivariable cost functions in model predictive control is the choice of weighting factors. Two finite control set model predictive control algorithms, applied to the three-phase active rectifier with an LCL filter, are described in the paper. The investigated algorithms, i.e. PCi_cu_c and PCi_gi_cu_c, implement multivariable approaches applying line (grid) current, capacitor voltage and converter current. The main problem dealt with in the paper is the choice of optimum values of the cost function weighting factors. The values of the factors calculated using the method proposed in the paper are very close to the values represented by the lowest THDi of the line current. Moreover, simulations verifying the equations used in the prediction of controlled values, i.e. line current, capacitor voltage and converter current, are presented. Both simulation and experimental results are presented to verify effectiveness of the investigated control strategies under change of the load (P = 5 kW and 2.5 kW), during transient states, under unbalanced and balanced line voltage.

The paper presents a novel model predictive flux control (MPFC) scheme for three-level inverter-fed sensorless induction motor drive operated in a wide speed region, including field weakening. The novelty of the proposed drive lies in combining in one system a number of new solutions providing important features, among which are: very high dynamics, constant switching frequency, no need to adjust weighting factors in the predictive cost function, adaptive speed and parameter (stator resistance, main inductance) estimation. The theoretical principles of the optimal switching sequence predictive stator flux control (OSS-MPFC) method used are also discussed. The method guarantees constant switching frequency operation of a three-level inverter. For speed estimation, a compensated model reference adaptive system (C-MRAS) was adopted while for IM parameters estimation a Q-MRAS was developed. Simulation and experimental results measured on a 50 kW drive that illustrates operation and performances of the system are presented. The proposed novel solution of a predictive controlled IM drive presents an attractive and complete algorithm/system which only requires the knowledge of nominal IM parameters for proper operation.

Most of the basic control methods of the grid-connected converter (GCC) are defined to work with a sine wave grid voltage. In that case if the grid voltage is distorted by higher harmonics, the grid current may be distorted too, which, in consequence, may increase the value of the THD of the grid voltage. The paper deals with an improved finite control set model predictive control (FCS-MPC) method of an LCL-filtered GCC operating under distorted grid conditions. The proposed method utilizes supplementary grid current feedback to calculate the reference converter current. The introduced signal allows to effectively improve the operation when the grid is subject to harmonic distortion. The paper shows a simulation analysis of the proposed control scheme operating with and without additional feedback under grid distortions. To validate the practical feasibility of the proposed method an algorithm was implemented on a 32-bit microcontroller STM32F7 with a floating point unit to control a 10 kW GCC. The laboratory test setup provided experimental results showing properties of the introduced control scheme.