This article proposes a model-free secondary voltage control (SVC) for microgrids (MG) using nonlinear multiple models adaptive control. Firstly, a linear robust adaptive controller is designed to guarantee the voltage stability in the bounded-input-bounded-output (BIBO) manner so as to meet the operation requirements of MGs. Secondly, a nonlinear adaptive controller is developed to improve the voltage tracking performance with the help of artificial neural networks (ANNs). A switching mechanism for coordinating such two controllers is designed to guarantee the closed-loop stability while achieving accurate voltage tracking. By an online identification based on the input and output data of MGs, the proposed method does not resort to any apriori information of system model and primary control, thus exhibiting good robustness, ease of deployment and disturbance rejection.

中文翻译：

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微型电网的非线性多模型自适应二次电压控制

本文提出了一种使用非线性多模型自适应控制的微电网（MG）的无模型二次电压控制（SVC）。首先，设计了一种线性鲁棒自适应控制器，以有界输入有界输出（BIBO）的方式保证电压的稳定性，从而满足了MG的工作要求。其次，开发了一种非线性自适应控制器以借助人工神经网络（ANN）改善电压跟踪性能。设计用于协调这两个控制器的开关机制，以确保闭环稳定性，同时实现精确的电压跟踪。通过基于MG的输入和输出数据的在线识别，所提出的方法不求助于任何方法先验 系统模型和主要控制的信息，因此具有良好的鲁棒性，易于部署和抗干扰性。