Predictive Current Control for Three-Level Four-Leg Indirect Matrix Converter under Unbalanced Input Voltage

In this paper, a robustness evaluation of model predictive current control with instantaneous reactive power minimization for a three-level four-leg indirect matrix converter is presented. Unbalanced voltages can be extremely dangerous, especially for motors and other inductive equipment. Unbalanced voltages can have a detrimental effect on equipment and the power system, which is exacerbated by the fact that a small phase voltage imbalance can result in a disproportionately large phase current imbalance. The robustness test is carried out by considering balance and unbalanced input voltages. The proposed control predicts the behavior of the load current and the instantaneous reactive power for every possible 96 switching states. Subsequently, it selects the optimum switching state which fulfils the objectives of the control without the need of modulators. The cost function has been adequately modified to consider the asymmetrical aspect of the input voltage. Experimental validation using a laboratory prototype was conducted by using FPGA under a wide range of input voltage unbalance. The experimental results show high fidelity load current reference tracking while maintaining relatively low instantaneous reactive power during the transient and steady-state condition. The percentage of reactive power after setting the optimal weighting factor, the average reactive power was found to reduce to approximately 10- 20%

Predictive-TOPSIS-based MPPT for PEMFC Featuring Switching Frequency Reduction

A maximum power point tracking (MPPT) for a proton exchange membrane fuel cell (PEMFC) using a combination of conventional finite control set model predictive control (FCS-MPC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is proposed in this paper. The key idea is to maximize the power generation from a PEMFC while minimizing the switching frequency of the power converter. The FCS-MPC technique is formulated to track the maximum power of PEMFC highly affected by ever-changing internal parameters. Meanwhile, the TOPSIS algorithm is applied to overcome the potential weaknesses of insulated-gate bipolar transistor (IGBT), which can only withstand a lower switching frequency. In this project, all simulations were run using MATLAB software to display the output power of the PEMFC system. As a result, the proposed predictive-TOPSIS-based MPPT algorithm can track the MPP for various PEMFC parameters within 0.019 s with an excellent accuracy up to 99.11%. The proposed MPPT technique has fast-tracking of the MPP locus, excellent accuracy, and robustness to environmental changes

Area Optimization for Networks-on-Chip Architectures using Deep Network Partitioning

This paper presents an area optimization for Network-on-Chip (NoC) architecture using deep Network Par- titioning technique. Among the hardest problems in NoC design is customizing the topological structure and application mapping on on-chip network in order to cater for application demand at minimal cost. The area cost of NoC is cut down by utilizing multi- level network partitioning where it partitions large networks into smaller segments. The enhancement in area cost is obtained by reducing both router area and the number of global links. In terms of performance, the multi-level network partitioning offers a better solution by assigning computational cores with heavy inter-core communications into the same segment. Therefore, the average inter-node distances would be minimized. This directly results in better performance due to its shortest path. For verification, the proposed technique has been tested on various System-on-Chip (SoC) applications case studies. The proposed technique results in the reduction of more than 7% router area, 19% global links, and 12% average inter-node distance

Predictive-TOPSIS based MPPT for PEMFC Featuring Switching Frequency Reduction

A maximum power point tracking (MPPT) for a proton exchange membrane fuel cell (PEMFC) using a combination of conventional finite control set model predictive control (FCS-MPC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is proposed in this paper. The key idea is to maximize the power generation from a PEMFC while minimizing the switching frequency of the power converter. The FCS-MPC technique is formulated to track the maximum power of PEMFC highly affected by ever-changing internal parameters. Meanwhile, the TOPSIS algorithm is applied to overcome the potential weaknesses of insulated-gate bipolar transistor (IGBT), which can only withstand a lower switching frequency. In this project, all simulations were run using MATLAB software to display the output power of the PEMFC system. As a result, the proposed predictive-TOPSIS-based MPPT algorithm can track the MPP for various PEMFC parameters within 0.019 s with an excellent accuracy up to 99.11%. The proposed MPPT technique has fast-tracking of the MPP locus, excellent accuracy, and robustness to environmental changes

Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System

This project aims to design a predictive maximum power point tracking (MPPT) for a proton exchange membrane fuel cell system (PEMFC). This predictive MPPT includes the predictive control algorithm of a DC-DC boost converter in the fully functional mathematical modeling of the PEMFC system. The DC-DC boost converter is controlled by the MPPT algorithm and regulates the voltage of the PEMFC to extract the maximum output power. All simulations were performed using MATLAB software to show the power characteristics extracted from the PEMFC system. As a result, the newly designed predictive MPPT algorithm has a fast-tracking of maximum power point (MPP) for different fuel cell (FC) parameters. It is confirmed that the proposed MPPT technique exhibits fast tracking of the MPP locus, outstanding accuracy, and robustness with respect to environmental changes. Furthermore, its MPP tracking time is at least five times faster than that of the particle swarm optimizer with the proportional-integral-derivative controller method

Model predictive current and reactive power control for multilevel four-leg indirect matrix converter / Hazrul Mohamed Basri

This thesis focused on model-based predictive current control which was applied to indirect matrix converter. Indirect matrix converter (IMC) is an alternative solution of conventional ac/ac converter. Its energy storage-less structure enables the construction of a compact power converter circuit. The feature of IMC was extended with multilevel concept to improve the output waveform quality by unifying the conventional four-leg indirect matrix converter with a four-switch circuit resembling a dual asynchronous buck-circuit to synthesise the multilevel output voltage. The unbalance voltage supply posed a real challenge in implementing the ac/ac power converter. In practice, the matrix converter is supplied by the utility grid which is prone to become unbalance due to the asymmetric load connected to the grid. Being energy storage-less solution, the unbalance voltage supply has a direct effect on the load current regulation due to the fluctuated active and reactive power. Hence, there is strong mutual coupling between the supply and the output. Any disturbance in the input voltages can be immediately reflected to the output voltages. For most of the modulation strategies, the unbalanced and non-sinusoidal input voltages can cause unwanted output harmonic voltages. This study is aimed to maintain excellent load current reference tracking while minimising the instantaneous reactive power for both balance and unbalance voltage supply. In order to achieve this objective, the conventional cost function was properly modified to adapt to the unbalance supply voltage. The predictive algorithm computes the one-step prediction load current and reactive power. The proposed control strategy uses the discrete nature of the system to predict the future load current and reactive power behaviour to perform switching optimisation using a minimum cost function criterion. This study proposed an optimized rectifier switching strategy to ensure positive fictitious dual dc-link voltage at any instant and reduce the computational burden of the controller. In order to evaluate the robustness of the proposed control, different combinations of balance or unbalance supply voltage with balanced or unbalanced loading conditions were pre-validated using Matlab/Simulink®. It is followed by an FPGA based experimental works to validate the proposed control scheme. The integration of this circuit has resulted in a significant reduction of current harmonics. the four-leg structure, the proposed topology was adequate for balance or unbalance load. Moreover, the modified cost function enabled an optimum reactive power minimisation throughout the wide range of voltage supply unbalance. The experimental assessment confirmed that the proposed control could cater for the wide range of degree of unbalance. In addition, it revealed an outstanding load current reference tracking with harmonics distortion below 5% while maintaining relatively small instantaneous reactive power. Findings from this study is that, subject to sufficient active power, outstanding load current tracking was achieved, and the instantaneous reactive power can be optimally reduced. The proposed system exhibit

Experimental evaluation of model predictive current control for a modified three-level four-leg indirect matrix converter

This study presents an experimental validation and robustness evaluation of predictive current control and reactive power minimisation strategy for a three-level three-phase four-wire indirect matrix converter. The proposed topology features a unification of conventional four-leg indirect matrix converter with an additional four switches circuit resembling a back-to-back buck circuit to synthesise multi-level variable dual dc-link voltage. A systematic rectifier switching strategy is elaborated to ensure positive fictitious dc-link voltage at any instant. The proposed control and topology have been tested under various transient and steady-state conditions for comprehensive robustness evaluation. The experimental results reveal an outstanding independent load current reference tracking with low ripple current and the reactive power minimisation has been achieved by tuning the weighting factor. The load current tracking and reactive power minimisation have been achieved by properly tuning the weighting factor. The load current harmonics distortion is recorded < 5% during normal operating conditions

Integrated Lens Microstrip-Slot Applicator for Breast Hyperthermia Procedure

Hyperthermia is an alternative procedure for cancer treatment. It has potential either used alone or adjuvant with other conventional procedures such as chemotherapy and radiotherapy to enhance the capability of chemotherapy drugs and the radiation intensity, respectively. However, since the success rate is still not significant, the requirements in improving the limitations for this alternative procedure are massively carried out. Therefore, in this paper, it is emphasised to improve the main deficiency of this hyperthermia treatment, which is focus position distance in order to reduce the possible adverse health effects due to the treatment by reducing the area of unwanted hot spots on surrounding healthy tissue. A simulation with SEMCAD X is utilised to obtain heat distribution on the treated tissue. Various rectangular microstrip-slot applicators have been modified and developed with SEMCAD X, where it is used to provide heat towards the treated tissue at a certain period of time and hyperthermia specific temperature. The outcomes showed the modified microstrip-slot with a Y shape is able to penetrate up to 80 mm with sufficient focus position distance. Finally, a water bolus is introduced to produce a cooling impact on the treated tissue, which also alters the effective field size (EFS) of heat dispersion