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• W4380758425 endingPage "110512" @default.
• W4380758425 startingPage "110512" @default.
• W4380758425 abstract "This paper presents a novel tuning method of a complex multiresonant current controller (MRCC). An online auto-tuning process is proposed to provide optimal coefficients suitable for the real-time operation of a grid-connected power converter. The time-consuming and inaccurate simulation stage based on the model of the plant is omitted. A novel function of constraints has been introduced into the optimization scheme to ensure the desired behavior of the control system. In this solution, the noise level of a control signal and the rise time of controlled currents are directly defined. To the author’s best knowledge, it is the first time when such a solution is proposed. Next, the most commonly used meta-heuristic optimization algorithms were applied to solve this particular optimization problem. Another original concept presented in the paper is the application of the disturbance-in-the-loop (DiL) approach. In this method, the distorted phase voltages are emulated during the tuning stage, and optimal coefficients of MRCC are selected in the off-grid operation of the power converter. The proposed solution ensures safe and efficient online tuning of the MRCC for an extremely simple performance index. As a result, the high-performance operation of the grid-connected inverter is achieved. A brief stability analysis based on Lyapunov’s stability theory is included. Experimental results obtained for grid-connected inverter indicate superior disturbance attenuation and current tracking. Advantages of the proposed approach are exhibited when compared to two analytical reference solutions." @default.
• W4380758425 created "2023-06-16" @default.
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• W4380758425 date "2023-09-01" @default.
• W4380758425 modified "2023-09-27" @default.
• W4380758425 title "Online auto-tuning of multiresonant current controller with nature-inspired optimization algorithms and disturbance in the loop approach" @default.
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• W4380758425 doi "https://doi.org/10.1016/j.asoc.2023.110512" @default.
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