Observer design typically demands a comprehensive understanding of the system's model, necessitating meticulous parameter tuning for each state. In this paper, we introduce an observer design tailored to a class of linear systems, mitigating the need for extensive tuning and intricate model knowledge. Our proposed observer integrates steady-state behavior estimation with a dynamic state-based estimation, effectively streamlining the design process. To illustrate its effectiveness, we apply this observer design to the control of running gears with inde-pendently rotating and driven wheels within the research project ‘Next Generation Train’. This approach demonstrates a significant reduction in the requisite tuning parameters and model intricacy, offering a more practical and efficient solution for control systems.