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 evidences 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.INDEX TERMS Deadbeat control, grid-connected inverter, current control, renewable energy sources.

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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.

Abstract-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.

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