## 1 Introduction  
Hydrogen is increasingly recognized as a key component in energy transition, offering a clean and renewable energy source that can significantly contribute to reducing global dependence on fossil fuels and mitigating climate change. Its role in decarbonizing various sectors is widely acknowledged, with applications spanning transportation, industrial production, and energy storage. [PERSON] et al. [1] reviewed the potential of hydrogen in energy transition and explored the development of green hydrogen technologies and efficient storage solutions. This aligned with global efforts to address climate change by reducing greenhouse gas emissions, a challenge that conventional energy sources are struggling to meet. Water electrolysis, used to produce hydrogen, represents a method for developing a sustainable energy system and reducing dependence on fossil fuels. This method not only converts renewable sources such as solar and wind power into storable and transportable hydrogen energy but also addresses the issue of supply instability. The advancement in water electrolysis technology contributes significantly to enhancing energy supply diversity and security, fostering technological innovation, and promoting the development of a green economy [2; 3]. However, temperature control during water electrolysis is important for ensuring the efficiency, performance, and safety of the electrolyzer. Proper temperature control not only maximizes energy conversion efficiency, reducing energy losses, but also prevents equipment damage and safety risks, extends equipment lifespan, and reduces long-term operational costs [4; 5; 6]. Thus, effective temperature control is a key factor in ensuring the stability, safety, and economic viability of the water electrolysis process. The main types of water electrolysis include alkaline water electrolysis, proton exchange membrane (PEM) electrolysis, and solid oxide electrolysis, each offering unique advantages and applications [7]. In this study, anion exchange membrane (AEM) electrolysis was utilized, a newer technology combining the benefits of traditional alkaline and PEM electrolysis. It provides a highly efficient and cost-effective method for hydrogen production using solid electrolyte membranes [8]. Various approaches for temperature control in water electrolysis systems include conventional proportional-integral-derivative (PID) control, fuzzy logic control (FLC), adaptive control, and predictive control. For example, [PERSON] et al. [9] utilized a proportional-integral (PI) controller and thermal circuit state feedback in their experiment. [PERSON] et al. [10] developed a dynamic model of a water-cooled fuel cell stack and simulated it with a PI controller in a state-space model. [PERSON] et al. [11] used conventional PID and optimized parameters through feedforward and adaptive PID parameter supply. [PERSON] et al. [12] addressed the slow response and poor dynamic performance by developing a dynamic temperature model for PEM fuel cells and proposing a control strategy based on the sparrow search algorithm PID. Moreover, FLC provides a robust and flexible framework for managing systems characterized by uncertainties, vagueness, and imprecision. This approach originated from [PERSON]'s influential 1965 paper on fuzzy sets [13], which introduced the groundbreaking concept of handling partial membership between 0 and 1. This innovation allows systems to represent degrees of truth instead of relying solely on rigid true/false binaries. The framework laid the foundation for the application of FLC in a wide array of dynamic and complex systems, where conventional control methods, dependent on precise inputs, often prove inadequate. In 1975, [PERSON] and [PERSON] [14] conducted a landmark experiment that marked the first practical implementation of an FLC controller, successfully modeling human-like reasoning and decision-making.