Abstract: China’s HL-3 Tokamak, the largest Tokamak in the country, has been designed to explore reactor-relevant plasma conditions. To achieve these high-performance regimes, elongated plasma configurations in the vertical direction are essential. However, elongated plasmas are inherently susceptible to the vertical displacement events (VDE), which pose a serious challenge to Tokamak operation. In the absence of reliable feedback control strategies, a VDE can rapidly evolve, leading to severe plasma instabilities that may cause the plasma to bombard the plasma-facing components within approximately 10 milliseconds. Such rapid events can result in excessive heat loads, material erosion, and potential damage to critical reactor components. Numerical simulations have been widely used to study VDE mitigation strategies, but traditional simulation approaches face inherent limitations. The complexity of plasma behavior in realistic experimental conditions makes it difficult for purely numerical models to accurately reproduce experimental results. Additionally, conducting mitigation studies directly on experimental Tokamaks is highly resource-intensive and poses significant operational risks. To address these challenges, in this paper, an innovative hardware-in-the-loop (HIL) simulation strategy for the study of plasma vertical displacement feedback control in the HL-3 Tokamak was introduced. In the proposed HIL framework, the plasma response and fast power supply dynamics were modeled using numerical modules. Meanwhile, the feedback control strategy was implemented in a physical controller, which was connected via real-time internet communication to the numerical modules. This hybrid approach effectively combines the advantages of both numerical simulations and physical experiments. The numerical modules provide a reliable and controllable plasma response, while the hardware-based controller ensures realistic real-world delays, disturbances, and data transmission effects. The framework enables the integration and testing of advanced control strategies, including proportional-integral-derivative (PID) control and model predictive control (MPC), which are commonly employed in modern plasma control systems. Comparative analysis between HIL simulation results and experimental data of HL-3 Tokamak demonstrates a high level of consistency, validating the accuracy and effectiveness of the proposed approach. Future research will focus on leveraging artificial intelligence (AI) techniques to enhance the efficiency and predictive capabilities of the HIL simulation. AI-driven approaches have the potential to accelerate feedback control optimization, improve response times, and enhance the robustness of vertical position control strategies.