A new predictive control scheme for a VSI with reduced common mode voltage operating at fixed switching frequency

Three-Vector-Based Low-Complexity Model Predictive Direct Power Control Strategy for PWM Rectifier Without Voltage Sensors

Abstract: A voltage sensorless control of low-complexity model predictive direct power control (LC-MPDPC) for pulsewidth modulation (PWM) rectifier is proposed. The conventional LC-MPDPC adopts one or two voltage vectors during one control period, which achieve good steady-state performance and quick dynamic response. In addition, based on the mathematical model of the real system, the conventional method only requires one prediction to find the optimal voltage vector, which reduces the control complexity and computational burden. However, the use of one or two vectors during one sampling interval presents abundant current harmonics and high power ripples, and the switching frequency is variable. In order to solve these problems while preserving all the advantages of the conventional LC-MPDPC, this paper presents a novel control scheme, with the aim of operating at a constant switching frequency and obtaining an excellent steady-state performance at a low switching frequency. The proposed method is based on an optimal application of three voltage vectors in a symmetrical way, which takes advantage of advanced PWM techniques. Furthermore, the virtual flux-based control scheme is introduced to achieve voltage sensorless control. The proposed strategy is compared with the conventional MPDPC methods and its effectiveness is confirmed by both simulation and experimental results from a three-phase PWM rectifier under 1000-W operation condition.

Model predictive controller with fixed switching frequency for a 3L-NPC inverter

Abstract: this paper introduces a new control scheme based on a Finite Set-Model Predictive Control (FS-MPC) and aims of a fixed switching frequency operation. The proposed scheme allows of obtaining a voltage vector that is responsible of nullifying the cost function's derivative for its optimization. Moreover, a closed-loop space vector modulation (SVM) based on the proposed predictive control scheme is introduced for a three-level grid connected inverter. The proposed algorithm that injects a desired current to the grid is investigated through external perturbations such as change in the line current amplitude as well as DC voltage variation. Discrete-time system model was developed and simulated. Simulation results on MATLAB/Simulink are provided to verify the fast dynamic performance, and good voltage balancing of DC bus capacitors of the NPC inverter.

Predictive Control for Microgrid Applications: A Review Study

Abstract: Microgrids need control and management at different levels to allow the inclusion of renewable energy sources. In this paper, a comprehensive literature review is presented to analyse the latest trends in research and development referring to the applications of predictive control in microgrids. As a result of this review, it was found that the application of predictive control techniques on microgrids is performed for the three control levels and with adaptations of the models in order to include uncertainties to improve their performance and dynamics response. In addition, to ensure system stability, but also, at higher control levels, coordinated operation among the microgrid’s components and synchronised and optimised operation with utility grids and electric power markets. Predictive control appears as a very promising control scheme with several advantages for microgrid applications of different control levels.

Model based predictive current control for a three-phase cascade H-bridge multilevel STATCOM operating at fixed switching frequency

Abstract: The absence of modulator in model based predictive control technique for different converter topologies generates a variable switching frequency that produces high frequency harmonics and higher stress on the power semiconductor devices. In this paper, a novel model based predictive control strategy with a fixed switching frequency applied to a three-phase cascade H-bridge multilevel STATCOM is introduced with the aim to increase the performance of classical model predictive control. Simulation results show increased performance of the proposed control method in terms of current waveform total harmonic distortion.

Modulated model predictive current control for H-bridge two-level single phase active power filters STATCOM

Abstract: Model predictive control techniques are characterized by a variable switching frequency which cause noise as well as large voltage and current ripple In this paper a predictive control strategy with a fixed switching frequency for a single-phase active power filter, namely modulated model predictive control, is proposed This technique produces modulated waveform at the output of the converter The feasibility of this strategy is evaluated using simulation results to demonstrate the advantages of predictive control, such as fast dynamic response and the easy inclusion of nonlinearities The constraints of the system are maintained but the performance of the system in terms of power quality is improved compared to the traditional model predictive control strategy

Model Predictive Control—A Simple and Powerful Method to Control Power Converters

Abstract: This paper presents a detailed description of finite control set model predictive control (FCS-MPC) applied to power converters Several key aspects related to this methodology are, in depth, presented and compared with traditional power converter control techniques, such as linear controllers with pulsewidth-modulation-based methods The basic concepts, operating principles, control diagrams, and results are used to provide a comparison between the different control strategies The analysis is performed on a traditional three-phase voltage source inverter, used as a simple and comprehensive reference frame However, additional topologies and power systems are addressed to highlight differences, potentialities, and challenges of FCS-MPC Among the conclusions are the feasibility and great potential of FCS-MPC due to present-day signal-processing capabilities, particularly for power systems with a reduced number of switching states and more complex operating principles, such as matrix converters In addition, the possibility to address different or additional control objectives easily in a single cost function enables a simple, flexible, and improved performance controller for power-conversion systems

Predictive Torque Control of Induction Machines Based on State-Space Models

Abstract: In this paper, we present a predictive control algorithm that uses a state-space model. Based on classical control theory, an exact discrete-time model of an induction machine with time-varying components is developed improving the accuracy of state prediction. A torque and stator flux magnitude control algorithm evaluates a cost function for each switching state available in a two-level inverter. The voltage vector with the lowest torque and stator flux magnitude errors is selected to be applied in the next sampling interval. A high degree of flexibility is obtained with the proposed control technique due to the online optimization algorithm, where system nonlinearities and restrictions can be included. Experimental results for a 4-kW induction machine are presented to validate the proposed state-space model and control algorithm.

Virtual-Flux-Based Predictive Direct Power Control of AC/DC Converters With Online Inductance Estimation

Abstract: This paper presents an improved predictive direct power control (P-DPC) algorithm for grid-connected three-phase voltage source converters without AC-side voltage sensors. The new algorithm is based on virtual-flux (VF) estimation and operates with constant switching frequency. Predictive controller selects in every sampling period appropriate voltage vector sequence and calculates duty cycles in order to minimize instantaneous active and reactive power errors. The theoretical principles of this algorithm are discussed, and selected experimental measurements and scope graphs that illustrate the operation and performance of the system are presented. It is shown that VF-P-DPC algorithm exhibits several advantages, particularly sinusoidal-grid-current low harmonic distortion even when grid voltage is distorted. In addition, the algorithm provides high dynamics at low switching frequency of 2 kHz.

Switching Frequency Reduction Using Model Predictive Direct Current Control for High-Power Voltage Source Inverters

Abstract: In this paper, a novel current control approach called model predictive direct current control (MPDCC) is presented. The controller takes into account the discrete states of the voltage source inverter (VSI), and the current errors are predicted for each sampling period. Voltage vectors are selected by a graph algorithm, whereby the most appropriate vector is chosen based on an optimization criterion. However, this depends on whether the state of the system is transient or steady. In the first case, the current error should be minimized as fast as possible in order to obtain fast dynamics. In the latter one, the VSI switching behavior is optimized since the switching losses account for a large amount of the total converter losses in high-power drive systems. MPDCC has been developed for a general neutral-point isolated resistive-inductive load with an internal voltage source. For demonstration, the presented control strategy has been implemented on a small-scale permanent-magnet synchronous machine drive system with a two-level VSI. This new approach has several advantages. The most important one is that the switching frequency is reduced up to 70% compared to linear control combined with pulsewidth modulation. Second, MPDCC obtains fast dynamic responses, which are already known from, e.g., direct torque control.