Chattering-Free Fixed-Time Robust Sliding Mode Controller for Grid-Connected Inverters Under Parameter Variations

This article proposes and experimentally validates a new chattering-free fixed-time robust sliding mode controller for the grid-connected three-phase two-level inverter through an RL filter. The proposed method addresses the reference trajectory tracking problem of grid current, enabling precise con...

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Bibliographic Details
Main Authors: Hosseinabadi, Pooyan Alinaghi, Mekhilef, Saad, Pota, Hemanshu R., Kermadi, Mostefa
Format: Article
Published: Institute of Electrical and Electronics Engineers 2024
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Online Access:http://eprints.um.edu.my/45684/
https://doi.org/10.1109/JESTPE.2023.3336186
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Summary:This article proposes and experimentally validates a new chattering-free fixed-time robust sliding mode controller for the grid-connected three-phase two-level inverter through an RL filter. The proposed method addresses the reference trajectory tracking problem of grid current, enabling precise control of the power injected into the grid. Advanced nonlinear sliding surfaces and control laws are designed with the primary objective of enhancing the robustness of the closed-loop system under the proposed controller. More specifically, this work concentrates on achieving robustness against variations in filter parameters and grid impedance. The control laws are formulated to alleviate chattering in the control signal. The notion of fixed-time stability is incorporated into the controller's design to ensure fixed-time convergence for both reaching and sliding phases and the ability to adjust the guaranteed settling time regardless of initial conditions. The fixed-time stability of the closed-loop system is proved using the Lyapunov theory. The simulation and experimental results validate the effectiveness of the proposed method. It demonstrates precise tracking capability and robust performance, especially when compared with a finite-time sliding mode controller and a conventional asymptotic sliding mode controller.