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

Output Voltage Improvement of a Matrix Converter under Unbalance and Distorted Input Voltage Using PR Controller

Matrix converter is an AC to AC converter without any energy storing element in the dc-link; therefore, any distortion in the input voltage directly affects the output voltage quality. In this paper, firstly, space vector modulation for direct matrix converter is discussed. Afterwards, a closed loop method without output voltage sensors is proposed in order to reduce the distortions in the output voltage. In the proposed method, output currents are measured and compared with their reference values, then, the error goes into a proportional resonant (PR) controller to determine the modulation index and angle of the output voltage. No need for output voltage sensors, simple implementation and low computational burden can be considered as the advantages of the proposed method. Although the method is presented for direct matrix converter, it can be adopted easily for indirect matrix converters. To show the effectiveness of the proposed method, comprehensive simulation tests are conducted and the obtained results are compared with previously proposed method

Preselection algorithm based on predictive control for direct matrix converter

This paper presents an enhanced predictive control strategy to reduce the calculation effort for direct matrix converters. The main idea is to preselect the switching states to decrease the calculation effort during each sample period. The proposed preselection algorithm enables a predefined cost function to consider only the preselected switching states to perform the expected control. On the basis of the preselection of switching states at each sample period, the proposed method can effectively reduce the calculation effort as well as show a good performance. The proposed predictive control scheme using only preselected switching states needed to generate the desired source/load current waveforms and control the input power factor. The feasibility of the proposed method is experimentally verified and results are presented in the paper

Error-voltage-based open-switch fault diagnosis strategy for matrix converters with model predictive control method

This paper proposes an error-voltage based open-switch fault diagnosis strategy for matrix converter (MC). A finite control set model predictive control (FCS-MPC) method is used to operate the MC. The MC system performances under normal operation and under a single open-switch fault operation are analyzed. A fault diagnosis strategy has also been implemented in two steps. First, the faulty phase is detected and identified based on a comparison of the reference and estimated output line-to-line voltages. Then, the faulty switch is located by considering the switching states of the faulty phase. The proposed fault diagnosis method is able to locate the faulty switch accurately and quickly without additional voltage sensors. Simulation and experimental results are presented to demonstrate the feasibility and effectiveness of the proposed strateg

Model predictive current control of grid-connected neutral-point-clamped converters to meet low-voltage ride-through requirements

The low-voltage ride through (LVRT) requirement demands the wind power plants to remain connected to the grid in the presence of grid voltage dips, actively helping the network overall control to keep network voltage and frequency stable. Wind power technology points to increase power ratings. Hence, multilevel converters, as for example, neutral-point-clamped (NPC) converters, are well suited for this application. Predictive current control presents similar dynamic response and reference tracking than other well-established control methods, but working at lower switching frequencies. In this paper, the predictive current control is applied to the grid-side NPC converter as part of a wind energy conversion system, in order to fulfill the LVRT requirements. DC-link neutral-point balance is also achieved by means of the predictive control algorithm, which considers the redundant switching states of the NPC converter. Simulation and experimental results confirm the validity of the proposed control approach.Postprint (author’s final draft

Introducing a New Hybrid Method to Reduce BLDC Motor Torque Ripple, Based on Predictive Control and Quasi Z-Source Converter

The commutation torque ripple adversely affects the performance of the six-phase inverter of the BLDC motor with trapezoidal back EMF and creates vibration and noise for industrial applications. In this paper, the motor model is obtained in non-commutation times and during the commutation period, and according to that, a suitable method to reduce the torque ripple, by equalizing the slope of the current disconnected from the motor and the slope of the current connected to the motor during commutation, is presented. At low speeds, torque ripple is reduced using predictive pulse width modulation technique. With this method, the duty cycle of the switch involved in the commutation is predicted and applied to the switch during the commutation intervals. At high speeds, this reduction is done using quasi z-source converter and selector circuit. The quasi z-source converter and the selector circuit increase the input voltage of the inverter during commutation intervals and increase its value to four times the back EMF voltage of the motor, thus reducing the torque ripple at high speeds. The theoretical and analytical results are verified using the simulations performed in the PLECS software

Model predictive MRAS estimator for sensorless induction motor drives

Ph. D. ThesisThe project presents a novel model predictive reference adaptive system (MRAS) speed observer for sensorless induction motor drives applications. The proposed observer is based on the finite control set-model predictive control principle. The rotor position is calculated using a search-based optimization algorithm which ensures a minimum speed tuning error signal at each sampling period. This eliminates the need for a proportional integral (PI) controller which is conventionally employed in the adaption mechanism of MRAS observers. Extensive simulation and experimental tests have been carried out to evaluate the performance of the proposed observer. Both the simulation and the experimental results show improved performance of the MRAS scheme in both open and closed-loop sensorless modes of operation at low speeds and with different loading conditions including regeneration. The proposed scheme also improves the system robustness against motor parameter variations and increases the maximum bandwidth of the speed loop controller. However, some of the experimental results show oscillations in the estimated rotor speed, especially at light loading conditions. Furthermore, due to the use of the voltage equation in the reference model, the scheme remains sensitive, to a certain extent, to the variations in the machine parameters. Therefore, to reduce rotor speed oscillations at light loading conditions, an adaptive filter is employed in the speed extraction mechanism, where an adaptation mechanism is proposed to adapt the filter time constant depending on the dynamic state of the system. Furthermore, a voltage compensating method is employed in the reference model of the MP-MRAS observer to address the problems associated with sensitivity to motor parameter variation. The performance of the proposed scheme is evaluated both experimentally and by simulation. Results confirm the effectiveness of the proposed scheme for sensorless speed control of IM drives