## 1 Introduction
Given the nonlinear and complex behavior of bridge structures during seismic events, traditional parameter-tuning methods often fail to identify globally optimal solutions. Consequently, intelligent optimization algorithms have gained traction in structural control applications. Among these, genetic algorithms are particularly effective in optimizing PID controller parameters due to their global search capabilities and independence from initial conditions [17; 18]. Genetic algorithms (GAs) simulate natural evolution by using operations such as selection, crossover, and mutation to explore the parameter space for a global optimum. As they do not rely on gradient information, GAs are well-suited for solving complex, nonlinear optimization problems. In active isolation systems, GAs can autonomously adjust PID controller parameters, allowing the system to maintain optimal performance under varying seismic conditions. This adaptive capability significantly enhances both the flexibility and seismic performance of active isolation systems [19]. Despite the superior performance of active isolation systems in seismic control, their complexity and reliance on external power sources limit their widespread adoption in certain applications. In response, semi-active and hybrid isolation systems have been developed [20; 21; 22]. These systems combine the benefits of both active and passive isolation approaches. Under normal seismic conditions, passive isolation devices manage seismic energy, while during extreme seismic events, the active control system is activated to further optimize the structural response [23; 24]. Semi-active isolation systems often utilize devices such as magneto-rheological (MR) dampers, which can adjust damping characteristics in real time without requiring significant power input [25; 26; 27]. MR dampers modify damping forces by varying the external magnetic field, enabling semi-active control with lower energy requirements. Hybrid isolation systems, however, integrate passive isolation with active control, offering a versatile solution capable of adapting to a wide range of seismic conditions. With advancements in computational technology and intelligent control methods, seismic design for bridges is increasingly moving towards greater adaptability and intelligence. The integration of active and passive isolation technologies not only improves the seismic resilience of bridge structures but also reduces system costs and energy consumption, enhancing robustness and reliability [28]. In high-seismic-risk regions, hybrid isolation systems can minimize operational disruptions while ensuring structural safety and maintaining post-earthquake functionality [29]. In many hybrid control systems, the interaction between active control forces and the passive control elements is often overlooked. This paper introduces a novel hybrid isolation system that integrates PID active control with passive isolation. The system accounts for the reactive forces generated by the PID controller on the passive isolation devices, while a GA is employed to optimize the PID parameters. This approach offers a new solution for bridge seismic protection by combining intelligent optimization with real-time control, significantly enhancing the system's flexibility, adaptability, and overall seismic performance. The main purpose of this paper is to propose a new hybrid isolation system and simulation method, and to analyze the performance of the isolation system when considering the reaction forces from the upper layer to the lower layer. This hybrid isolation system can be applied not only to bridges but also to buildings, precision instruments, and cultural relics.