Abstract
In this study, an adaptive fuzzy-neural-network-imitating sliding-mode control (AFNNISMC) is developed for a parallel-inverter system in an islanded micro-grid (MG) via a master-slave current sharing strategy. For ensuring the system-level stability, an entire dynamic model is constructed by viewing the parallel-inverter system as a whole. First, a total sliding-mode control (TSMC) scheme, and the TSMC plus an adaptive observer to form an adaptive TSMC (ATSMC) framework are designed for the parallel-inverter system. Then, a four-layer fuzzy neural network (FNN) is investigated to imitate the TSMC law to improve the system robustness, overcome the drawback of the dependence on detailed system dynamics, and deal with the chattering phenomena caused by the TSMC. According to the Lyapunov stability theorem and the projection algorithm, network parameters in the FNN are regulated online by employing the approximation error between the FNN and the TSMC law to ensure the convergence of the network and the stability of the control system. Thereby, the performance of high power quality and high-precision current sharing between inverters can be guaranteed even if system uncertainties exist. Moreover, the proposed AFNNISMC system can achieve the seamless disconnection and re-connection of slave inverters from and into an energized parallel-inverter system, which improves the redundancy and operation flexibility. In addition, numerical simulations and experimental results are given to demonstrate the feasibility and effectiveness of the proposed AFNNISMC scheme. Furthermore, performance comparisons with the ATSMC strategy and a conventional proportional-integral control (PIC) framework are provided to verify the superiority of the proposed scheme.
Highlights
For the feature of low emissions and high energy efficiency, distributed generation sources (DGs) have attracted great attention as renewable sources [1], [2]
In this study, a model-free adaptive fuzzy-neural-networkimitating sliding-mode control (AFNNISMC) with a master-slave current sharing strategy is proposed for a parallel-inverter system in an islanded micro-grid (MG)
An adaptive total sliding-mode control (ATSMC) law for the parallelinverter system with global robustness can be obtained by combining an adaptive observer for the control gain of the curbing controller into the total sliding-mode control (TSMC)
Summary
For the feature of low emissions and high energy efficiency, distributed generation sources (DGs) (e.g., wind generator, photovoltaic, etc.) have attracted great attention as renewable sources [1], [2]. The motivation of this study is to design a model-free control strategy for the parallel-inverter system with a master-slave current sharing scheme in an islanded MG, realize the accurate voltage tracking and current sharing both under the occurrence of parameter variations and structure uncertainties, and ensuring the system-level stability with global robustness. Theorem 2: If the curbing controller (uc) in (10a) is replaced by uca in (13a) with an adaptive observer for the bound of the system uncertainty vector designed in (13b), the stability of the designed ATSMC system with the control law uATSMC = ub + uca for the parallel-inverter system with the master-slave current sharing control scheme can be guaranteed. The design of the proposed AFNNISMC framework will be described
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