A modulated model predictive control scheme for the brushless doubly-fed induction machine

This paper proposes a modulated model predictive control (MMPC) algorithm for a brushless double-fed induction machine. The Brushless Doubly-Fed Induction Machine has some important advantages over alternative solutions for brushless machine applications. The proposed modulation technique achieves a fixed switching frequency, which gives good system performance. The paper examines the design and implementation of the modulation technique and simulation results verify the operation of the proposed modulation technique

Effective Torque Ripple Reduction of Permanent Magnet Brushless DC Motor

To reduce commutation torque ripple, a model predictive control (MPC) for permanent brushless DC motors (BLDCM) is presented (CTR). Torque ripples cause vibration noise and decrease efficiency. The suggested MPC system is constructed by forecasting the phase current with the aim of minimizing the BLDCM\u27s CTR and taking into consideration the CTR sources. The method presented in this paper is a unique methodology for suppressing CTR over the whole speed range, avoids more complex current controllers or modulation models, and overcomes the challenges of commutated-phase-current control. The ideal switching state is instantly selected and implemented during the next sample period according to the preset cost function in order to match the slope rates of outgoing and incoming phase currents during commutation, ensuring the minimum of commutation torque ripple. The modelling and experiment findings show that the suggested method can effectively reduce CTR over a wide speed range and achieve the better CTR minimization performance. The results are then compared to the outcomes of various torque ripple reduction(TRR) techniques

Model Predictive Controlled Active NPC Inverter for Voltage Stress Balancing among the Semiconductor Power Switches

© Published under licence by IOP Publishing Ltd. This paper presents a model predictive controlled three-level three-phase active neutral-point-clamped (ANPC) inverter for distributing the voltage stress among the semiconductor power switches as well as balancing the neutral-point voltage. The model predictive control (MPC) concept uses the discrete variables and effectively operates the ANPC inverter by avoiding any linear controller or modulation techniques. A 4.0 kW three-level three-phase ANPC inverter is developed in the MATLAB/Simulink environment to verify the effectiveness of the proposed MPC scheme. The results confirm that the proposed model predictive controlled ANPC inverter equally distributes the voltage across all the semiconductor power switches and provides lowest THD (0.99%) compared with the traditional NPC inverter. Moreover, the neutral-point voltage balancing is accurately maintained by the proposed MPC algorithm. Furthermore, this MPC concept shows the robustness capability against the parameter uncertainties of the system which is also analyzed by MATLAB/Simulink

Integration of inverter constraints in geometrical quantification of the optimal solution to an MPC controller

Published Conference ProceedingsThis paper considers a model predictive controller with reference tracking that manipulates the integer switch positions of a power converter. It can be shown that the optimal switch position can be computed without solving an optimization problem. Specifically, in a new coordinate system, the optimization problem can be solved offline, leading to a polyhedral partition of the solution space. The optimal switch position can then be found using a binary search tree. This concept is exemplified for a three-level single-phase converter with an RL load

Sequential model predictive control of direct matrix converter without weighting factors

© 2018 IEEE. The direct matrix converter (MC) is a promising converter that performs direct AC-to-AC conversion. Model predictive control (MPC) is a simple and powerful control strategy for power electronic converters including the MC. However, weighting factor design and heavy computational burden impose significant challenges for this control strategy. This paper investigates the sequential MPC (SMPC) for a three-phase direct MC. In this control strategy, each control objective has an individual cost function and these cost functions are evaluated sequentially based on priority. The complex weighting factor design process is not required and the computational burden can be reduced. In addition, specifying the priority for control objectives can be achieved. A comparative simulation study with standard MPC is carried out in Matlab/Simulink. Control performance is compared to the standard MPC and found to be comparable. Simulation results verify the effectiveness of the proposed strategy

Model predictive direct power control of three-level T-type inverter-fed doubly-fed induction generator for wind energy system

The paper proposes a simplified direct power control strategy of a doubly-fed induction generator fed by a three-level T-type inverter based on finite control set model predictive control. A mathematical model based on grid voltage orientation was employed to determine the predictive values of the stator flux, rotor current, and capacitor voltages for all feasible rotor-side inverter output voltages. The active and reactive powers were calculated by using the grid voltage and the rotor current. A cost function was applied to track the active and reactive powers, maintain the balance of capacitor voltages, and reduce the common-mode voltage. The best switching control input was chosen by minimizing the cost function and implemented to the inverter. Different operating conditions of wind turbine systems were studied with Matlab/Simulink environment. The simulation results validate the improved performance of the proposed method compared with the classical control in terms of transient response and steady-state conditions

Predictive voltage control of direct matrix converter with reduced number of sensors for the renewable energy and microgrid applications

© 2017 IEEE. This work proposes and investigates a renewable energy distributed generation system involving a matrix converter with an output filter working as a stable voltage supply. This is especially relevant for the stand-alone operation of a renewable energy microgrid where a stable sinusoidal voltage with prescribed amplitude and frequency under various load conditions is the main control objective. A controllable input power factor is preferred. In this paper, the model predictive control is employed to regulate the matrix converter output voltages which in turn are the supply for systems of the following stage. To reduce the number of required measurements and sensors, the work designs observers and makes use of the switch matrix. In addition to the regulation of the sinusoidal output voltages and input power factor, the control scheme deals with the common-mode voltage. The switching frequency is also considered in the controller to reduce the switching losses and keep the average switching frequency constant. In addition, the voltage transfer ratio can be improved at the cost of input current distortion. Supplying DC loads is feasible with this proposed control method. The controller is tested under various conditions including non-linear loads, DC loads and unbalanced input conditions to show it is effective, simple and easy to implement. Simulation results corroborate the effectiveness of the proposed controller and applications

Investigation of Grid-Connected and Islanded Direct Matrix Converter for Renewable Microgrid Applications with Model Predictive Control

© 2018 IEEE. The direct matrix converter has been proposed for many potential applications. However, it remains unexplored within the context of microgrids and distributed generation. This paper investigates the application of the direct matrix converter to these areas. Both the grid-connected and islanded operation modes are explored. Model predictive control is employed to achieve flexible active and reactive power regulation in the grid-connected mode, and stable sinusoidal voltage control in the islanded mode. It is also used to achieve grid voltage synchronization prior to grid connection. Simulation and experimental results verify the feasibility and effectiveness of the direct matrix converter when used in grid-connected and islanded microgrids. When used in the matrix converter-connected microgrid, model predictive control is effective in regulating the voltage and the power exchange with the grid

Finite control set model predictive control for grid-tied quasi-Z-source based multilevel inverter

In this paper, a finite control set Model Predictive Control (MPC) for grid-tie quasi-Z-Source (qZS) based multilevel inverter is proposed. The proposed Power Conditioning System (PCS) consists of a single-phase 2-cell Cascaded H-Bridge (CHB) inverter where each module is fed by a qZS network. The aim of the proposed control technique is to achieve grid-tie current injection, low Total Harmonic Distortion (THD) current, unity power factor, while balancing DC-link voltage for all qZS-CHB inverter modules. The feasibility of this strategy is validated by simulation using Matlab/Simulink environment