Disturbance‐Resilient Voltage/Power‐Quality Management for Islanded Inverters Using Self‐Tuning Type‐3 Fuzzy Controller

ABSTRACT This paper proposes a disturbance‐resilient adaptive fuzzy sliding‐mode control (AFSMC) strategy for off‐grid (islanded) inverters using an interval type‐3 (IT3) fuzzy logic system (FLS). An integral sliding surface is formulated to eliminate the reaching phase and ensure robust output‐voltage regulation under lumped uncertainties. A model‐based inductor‐current reference with an embedded limiter is incorporated to provide overcurrent protection during abnormal operating conditions. To mitigate the chattering associated with conventional sliding‐mode switching and to avoid relying on tight uncertainty bounds, the discontinuous term is replaced by a continuous IT3‐FLS compensator. The rule weights, membership‐function (MF) parameters of the IT3‐FLS, and translation width are tuned online via Lyapunov‐based adaptation laws. Comparative simulations and real‐time co‐simulation under load variations, DC‐link fluctuations, filter‐parameter perturbations, and master–slave inverter connection/disconnection events demonstrate improved tracking and power quality. The proposed controller reduces output‐voltage THD to 0.81% (vs. 1.59% for SMC and 4.85% for PID) and lowers the control‐input chattering index from to , while achieving up to 76.4% improvement in voltage MSE at the disturbance instant under parameter variations. The resulting IT3‐FLS‐based controller provides a practical and extensible framework for uncertain nonlinear power‐electronic systems, with potential applicability to motor drives and related converter‐based applications.

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Publication Details

Journal
Energy Science & Engineering
Published
2026-03-22
DOI
https://doi.org/10.1002/ese3.70507
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
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article

Disturbance‐Resilient Voltage/Power‐Quality Management for Islanded Inverters Using Self‐Tuning Type‐3 Fuzzy Controller

Junbo Mao, Ruslan Omirgaliyev, Du Changdong, Nurkhat Zhakiyev et al.
Energy Science & Engineering
Microgrid Control and Optimization
article

Disturbance‐Resilient Voltage/Power‐Quality Management for Islanded Inverters Using Self‐Tuning Type‐3 Fuzzy Controller

Junbo Mao, Ruslan Omirgaliyev, Du Changdong, Nurkhat Zhakiyev, Ardashir Mohammadzadeh, Didar Yedilkhan, Amirhossein Khosravi Sarvenoee, Man‐Wen Tian
article en

Abstract

ABSTRACT This paper proposes a disturbance‐resilient adaptive fuzzy sliding‐mode control (AFSMC) strategy for off‐grid (islanded) inverters using an interval type‐3 (IT3) fuzzy logic system (FLS). An integral sliding surface is formulated to eliminate the reaching phase and ensure robust output‐voltage regulation under lumped uncertainties. A model‐based inductor‐current reference with an embedded limiter is incorporated to provide overcurrent protection during abnormal operating conditions. To mitigate the chattering associated with conventional sliding‐mode switching and to avoid relying on tight uncertainty bounds, the discontinuous term is replaced by a continuous IT3‐FLS compensator. The rule weights, membership‐function (MF) parameters of the IT3‐FLS, and translation width are tuned online via Lyapunov‐based adaptation laws. Comparative simulations and real‐time co‐simulation under load variations, DC‐link fluctuations, filter‐parameter perturbations, and master–slave inverter connection/disconnection events demonstrate improved tracking and power quality. The proposed controller reduces output‐voltage THD to 0.81% (vs. 1.59% for SMC and 4.85% for PID) and lowers the control‐input chattering index from to , while achieving up to 76.4% improvement in voltage MSE at the disturbance instant under parameter variations. The resulting IT3‐FLS‐based controller provides a practical and extensible framework for uncertain nonlinear power‐electronic systems, with potential applicability to motor drives and related converter‐based applications.

Energy Science & Engineering
Sakarya University (TR), Harvard University Press (US), Astana Medical University (KZ), Xiangtan University (CN)
Openalex Percentile: Top 12%
Microgrid Control and Optimization
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