<p>Magnetic suspension systems are widely used in engineering applications, such as maglev transportation and precision manufacturing, due to their frictionless and highly controllable characteristics. However, their inherent nonlinearity and fractional-order dynamics pose significant challenges in control design. This paper proposes an optimal position-tracking controller for the magnetic suspension system. As a complex nonlinear system with fractional-order components, the magnetic suspension system is modeled as a fractional-order ultra-local model. Via fractional-order time-delay estimation strategy, the lumped disturbances in the model are estimated and eliminated. Subsequently, an error convergence strategy based on fractional-order sliding mode and the Lyapunov equation is developed. Furthermore, to avoid brief oscillations of the system for discontinuous signals, an event-triggered mechanism is designed. Before the event-triggering condition being met, the system is controlled solely by the FO-PID. Finally, the optimal parameters of the controller are determined using the Hippopotamus Optimization algorithm. To validate the effectiveness of the proposed algorithm, the experiment is conducted on SolidWorks–MATLAB simulation platform. Under different types of inputs and noise disturbances, the proposed algorithm exhibits higher tracking accuracy and enhanced disturbance rejection capability compared to other methods.</p>