## 1 Introduction  
As offshore wind power has the noticeable advantages of high efficiency, cleanliness, and nontoxicity, countries around the world are actively deploying offshore wind power hydrogen production stations to reduce their dependence on fossil fuels [1, 2]. On the other hand, versatile hydrogen has great potential to be combined with offshore wind energy and thus becomes one of the pillars of a completely decarbonized energy strategy [3, 4, 5]. Among the various forms of hydrogen utilization, hydrogen fuel cells are deemed the most promising ones that can produce great value in the task of peak shaving in offshore wind energy systems. The solid oxide fuel cell (SOFC) is the most extensively researched hydrogen fuel cell that has received a lot of attention due to its high energy conversion efficiency and the ability to provide high-quality residual heat [6, 7]. Recently, the SOFC has been endowed with special functions in various industrial production scenarios [8], most notably, to be used to solve the problem of offshore wind power buffering. However, the interior mechanism of SOFC systems is complex and sophisticated with strong nonlinearity and high sensitivity to disturbance. Accordingly, reliable control of the system output voltage not only has a great influence on the output power quality but also is critical to the connection of offshore wind power generation to the grid. Therefore, it is urgent to introduce more reliable control strategies to improve the output voltage stability of fuel cell systems. Many countries have carried out related research works. Combined with the feed-forward decoupling method, [PERSON] et al. [9] proposed a fuzzy PID controller for the proton exchange membrane fuel cell (PEMFC) air supply system. The results show that the decoupling fuzzy PID control method is obviously superior to other methods regarding the adaption to varying operating conditions. Orienting on the object of the hydrogen fuel cell stack, [PERSON] et al. [10] tried to model the electrical characteristics of the power supply part and thus tackle the barrier of rectifying the operating parameters. [PERSON] et al. [11] proposed a controller that combined multiple PI and PID subcontrollers to achieve quick responses to demand change. [PERSON] et al. [12] proposed a control model with unmodeled dynamic compensation for SOFC systems and compared it with the traditional sliding mode controller; the results showed that the proposed model behaves well in controlling temperature and pressure. However, the above works ignore the influence of disturbance, which can greatly deteriorate the control performance of SOFC systems in real working conditions. Aiming to overcome disturbance influence, the active disturbance rejection control (ADRC) is introduced and has been proven to be effective in suppressing disturbance influence. Traditional PI and PID controllers are inapplicable to ensure system stability in case of unknown strong disturbance. While ADRC is a promising controller, it has the advantages of fast response, small overshoot, and robustness [13; 14; 15], and thus has been widely used in various fields. [PERSON] et al. [16] established a dynamic water management model for the PEMFC system, expecting to balance the cathode humidity of PEMFC through the ADRC technique. Compared with PID or fuzzy PID controllers, ADRC can diminish overshooting and enhance efficiency. Considering the nonlinear voltammetry characteristics of fuel cells, [PERSON] et al. [17] designed an ADRC-based adaptive controller, and the results suggest that the method has stronger robustness against unknown perturbations compared with a conventional ADRC controller. However, there are too many parameters in ADRC that need to be elaborately tuned, which is time-consuming and requires professional knowledge. Therefore, it is significant if ADRC parameters can be adaptively optimized. There are a variety of methods proposed to solve the multiobjective optimization problem, e.g., for multiparameter controllers.