Islanded microgrids (MGs) are now widely used to electrify rural areas at a lesser cost and with greater efficiency. To maintain system balance and guarantee stability when exposed to various disturbances, MGs should be equipped with efficient controllers. Traditional controllers (like the PI controller) are linear and offer the best performance at a certain operating point, but the performance may degrade when the operating situation changes. To mitigate the drawbacks of fixed parameters controller, the paper suggested a fuzzy PI controller-based model reference adaptive control (FPI-MRAC) optimized by an advanced meta-heuristic optimization technique coronavirus herd immunity optimizer (CHIO) for enhancing the dynamic performance of several interconnected MGs. The proposed controller is non-linear adaptive controller that can improve the system performance over a wide range of operating conditions. The effectiveness of FPI-MRAC is assessed by subjecting the system to various disturbances, such as generation variation, load change, changing in uncertain system parameters and occurrence short circuit faults. Additionally, it investigated how quick reaction supercapacitors can improve the dynamic performance of the system. The acquired results show that, for all applied scenarios, the FPI-MRAC offers a much superior dynamic response than PI controller. Using super-capacitors also improves the system frequency when there are disruptions.