Radial Basis Function-Based Super-Twisting Sliding Mode Current Control for Single-Phase Grid-Tied Inverters
Received: 26 March 2026 | Revised: 5 May 2026, 12 May 2026, and 19 May 2026 | Accepted: 20 May 2026 | Online: 3 June 2026
Corresponding author: Nhat Tung Nguyen
Abstract
This paper proposes a current control strategy for a single-phase grid-tied inverter under conditions of parameter uncertainty and disturbance. Inductance and filter resistance deviations degrade the performance of traditional model-based control methods. To overcome this, a Radial Basis Function (RBF) neural network is used as an online observer to approximate and compensate for aggregate errors due to uncertainty and unmodeled dynamics. Simultaneously, Super-Twisting Sliding Mode Control (STSMC) is applied to reduce the chattering phenomenon and ensure finite-time convergence with a continuous control signal. The RBF–STSMC combination reduces conservatism in parameter selection and enhances system robustness. Stability is demonstrated using Lyapunov, and MATLAB/Simulink simulation results show superior performance compared to traditional SMC and PID controllers.
Keywords:
single-phase grid-tied inverter, Super-Twisting Sliding Mode Control (STSMC), advanced sliding mode control, Radial Basis Function (RBF) neural network, Lyapunov stabilityReferences
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