Discrete-time dynamic systems demonstrate quite exciting possibilities from the perspective of control as compared with the continuous-time counterpart. Interesting properties of discrete-time dynamic systems include the possibility to algebraically determine previously unknown system parameters by simply measuring the present inputs and outputs of the system. Additionally, achieving a finite settling time with zero steady-state error is only achievable in discrete-time dynamic systems. Deadbeat current control (DBCC) has been used to achieve a finite settling time, especially in grid-connected inverter applications. However, there is no comprehensive study on reviewing or evaluating existing control approaches, to the authors’ best knowledge. This paper systematically examined the existing methods by paying attention to four key research issues: 1) research evidence indicating the adoption of DBCC in grid-connected inverter applications (GCIAs), 2) the types of deadbeat control approaches adopted in GCIAs, 3) the best approach in terms of stability especially regarding grid-impedance variation, and 4) the barriers that might prevent the wide adoption of DBCC in GCIAs. Finally, this paper presents a hypothesis based on the simulated results on which approach is superior at present to give readers a direction for further research classification on deadbeat control.

The control of grid‐connected inverters is recently executed with digital microprocessors due to the advances in digital signal processing technology. However, the digital realisation has a drawback of the phase lag induced by the time‐delay. This phase lag challenges the stability and robustness of the controller of the inverters. In view of the challenge, this paper presents a comprehensive review of time‐delay compensation techniques employed in both model‐free (MF), and model‐based (MB) controls of an inverter in grid connection. MF techniques mainly use proportional‐integral, and proportional resonance controllers with some techniques to reduce time‐delay. Meanwhile, for MB, this paper discusses the commonly used control techniques, which are the Smith predictor, modified Smith predictor, deadbeat controller and model predictive controller. Several related techniques from the literature that have been adopted to mitigate the delays are tabulated comprehensively, and critical issues regarding the MF and MB techniques are also discussed. Finally, this paper presents a hypothesis on which technique is superior at present and suggests a hybrid technique from the MF and MB techniques to give readers a direction for further research.

The current paradigm in integrating intermittent renewable energy sources into microgrids presents various technical challenges in terms of reliable operation and control. This paper performs a comprehensive justification of microgrid trends in dominant control strategies. It covers multilayer hierarchical control schemes, which are able to integrate seamlessly with coordinated control strategies. A general overview of the hierarchical control family that includes primary, secondary, tertiary controls is presented. For power sharing accuracy and capability, droop and non-droop-based controllers are comprehensively studied to address further development. The voltage and frequency restoration techniques are discussed thoroughly based on centralized and decentralized method in order to highlights the differences for better comprehend. The comprehensive studies of grid synchronization strategies also overviewed and analyzed under balanced and unbalanced grid conditions. The details studies for each control level are displayed to highlight the benefits and shortcomings of each control method. A future prediction from the authors’ point of view is also provided to acknowledge which control is adequate to be adopted in proportion to their products applications and a possibility technique for self-synchronization is given in this paper.

The growing trend for electric vehicles (EVs) and fast-charging stations (FCSs) will cause the overloading of grids due to the high current injection from FCSs’ converters. The insensitive nature of the state of charge (SOC) of EV batteries during FCS operation often results in grid instability problems, such as voltage and frequency deviation at the point of common coupling (PCC). Therefore, many researchers have focused on two-stage converter control (TSCC) and single-stage converter (SSC) control for FCS stability enhancement, and suggested that SSC architectures are superior in performance, unlike the TSCC methods. However, only a few research works have focused on SSC techniques, despite the techniques’ ability to provide inertia and damping support through the virtual synchronous machine (VSM) strategy due to power decoupling and dynamic response problems. TSCC methods deploy current or voltage control for controlling EVs’ SOC battery charging through proportional-integral (PI), proportional-resonant (PR), deadbeat or proportional-integral-derivative (PID) controllers, but these are relegated by high current harmonics, frequency fluctuation and switching losses due to transient switching. This paper reviewed the linkage between the latest research contributions, issues associated with TSCC and SSC techniques, and the performance evaluation of the techniques, and subsequently identified the research gaps and proposed SSC control with SOC consideration for further research studies.

This paper presents the performance of the Arduino microcontroller board in response to an advanced control strategy for a motor control application. Two set of control theories have been used and combined as known as the Proportional Integration (PI) - Repetitive controller. This controller has been designed in MATLAB-Simulink environment and then downloaded to the Arduino for testing. The test set consists of 3 phase inverter, filter, induction machine (IM) and a set of current controller. The feedback current from the IM will be the control parameter for the controller and the Arduino in order to generate the pulse width modulation (PWM) pattern. Different PWM pattern is generated when the feedback current is changing due to the changing of the load.