This paper presents the dynamic modeling and parameter identification of an industrial actuator known as a voice coil proportional valve. This actuator is crucial for precise position control in industrial hydraulic cylinders, particularly when high accuracy, smooth motion, high speed, and acceleration are required. Accurate parametric modeling of the system is essential for effective control and monitoring. However, identifying the physical parameters of this model is challenging due to its nonlinear parameter dependencies, rendering traditional least-squares methods unsuitable. To address this, the Levenberg-Marquardt algorithm is proposed as a solution for nonlinear parameter identification. Both simulations and experimental data are employed to validate the proposed continuous parametric model. Despite the presence of noisy data, the results demonstrate the effectiveness of the proposed approach.