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Optimally scheduling alkaline electrolyzers (AELs) in a hydrogen-based microgrid (HBM) can greatly unleash the operational flexibility of the HBM. However, existing scheduling strategies of AELs mostly utilize a simplified AEL model, which ignores the nonlinear coupling of electric-hydrogen-thermal sectors, violating the AEL's security constraints thereby making the scheduling scheme infeasible. This paper proposes an improved model predictive control (MPC) based optimal scheduling framework which incorporates a scheduling correction algorithm into the basic MPC structure. This framework is utilized for implementing economic and resilient scheduling of an HBM under normal and emergency conditions, respectively. With the scheduling correction algorithm, this framework can be formulated into a computationally efficient mixed-integer linear programming, meanwhile guaranteeing the solutions strictly satisfy the security constraints of hydrogen facilities (i.e. AEL and hydrogen tank). Case studies are conducted based on real operating data of a Danish energy island Bornholm. The results demonstrate that the proposed scheduling scheme under normal conditions can contribute to significant comprehensive benefits from the daily operation cost saving of 68%, computational time saving of 98%, and satisfying the security constraints of hydrogen facilities, compared to previous scheduling strategies. Besides, it sharply reduces load shedding under emergency conditions by proactively allocating distributed energy sources in the HBM. • A novel economic and resilient scheduling scheme is presented for microgrids. • An improved electrolyzer model is built to precisely predict its state evolution. • A computationally efficient solving algorithm is proposed via an improved MPC. • The scheduling cost is saved by 68%, within the security of hydrogen facilities. • The scheduling scheme maintains the supply for critical loads during extreme events. [ABSTRACT FROM AUTHOR]