This study investigates the experimental validation of finite control set–predictive current control (FCS‐PCC) of a multi‐level four‐leg voltage‐source inverter (VSI) operating under balanced and unbalanced conditions. The proposed topology is a combination of conventional four‐leg VSI with an additional four switches circuit serving as dc voltage synthesiser. Unification of both circuits can supply energy to unbalanced three‐phase loads by providing the path for a zero‐sequence load while maintaining appropriate load voltage to the system. The proposed control strategy takes advantage of the discrete nature of the power converter system to predict the future behaviour of the output current. FCS‐PCC is based on an optimal approach that selects the most accurate switching signals among 48 valid switching states by computing cost function and applying switching state that minimises the tracking error to the next sampling time. The proposed control has been experimentally verified to assert the robustness of the control. The prominent outcomes of the experiments confirm the ability of independent load current reference tracking with harmonics distortion lower than the conventional eight switches VSI.

In a photovoltaic (PV)-battery integrated system, the battery undergoes frequent charging and discharging cycles that reduces its operational life and affects its performance considerably. As such, an intelligent power control approach for a PV-battery standalone system is proposed in this paper to improve the reliability of the battery along its operational life. The proposed control strategy works in two regulatory modes: maximum power point tracking (MPPT) mode and battery management system (BMS) mode. The novel controller tracks and harvests the maximum available power from the solar cells under different atmospheric conditions via MPPT scheme. On the other hand, the state of charge (SOC) estimation technique is developed using backpropagation neural network (BPNN) algorithm under BMS mode to manage the operation of the battery storage during charging, discharging, and islanding approaches to prolong the battery lifetime. A case study is demonstrated to confirm the effectiveness of the proposed scheme which shows only 0.082% error for real-world applications. The study discloses that the projected BMS control strategy satisfies the battery-lifetime objective for off-grid PV-battery hybrid systems by avoiding the over-charging and deep-discharging disturbances significantly.

<span>This paper presents the microstrip antenna with different applied frequencies used as a non-invasive hyperthermia applicator. This non-invasive hyperthermia applicator is introduced to clarify the sufficient heat distribution on the treated tissue for different breast cancer stages. 57 mammogram breast cancer images from early-stage to stage-3 are analyzed to obtain the required penetration depth and focus position distance. Then, the simulation-based experiment is carried out to observe the heating distribution on different stages of cancer with two different operating frequencies; 915MHz and 2450MHz. Also included in this paper is the prediction on the period for hyperthermia treatment planning execution. Based on the results, various penetration depths are obtained when different operating frequencies are applied. 915MHz antenna showed better results when compared to 2450MHz, where microstrip applicator with 915MHz is able to heat cancer at stage-1, stage-2, and stage-3 with good penetration depth and focus position distance, while 2450MHz only performed well in early-stage cancer. Meanwhile, different stages require various periods of time. From the results, the shortest period for hyperthermia execution simulated in the early-stage and then followed by stage-3, stage-2, and the longest period is in stage-1.</span>

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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%.