# Steering Dynamic and Hybrid Steering Control of a Novel Micro-Autonomous Railway Inspection Car
## 5 Conclusions  
The hybrid steering control system of the new micro-autonomous railway inspection vehicle was developed with the goal of substantially enhancing test performance and operational stability. In the SIMPACK and SIMULINK models, the lateral dynamics of the vehicle were simulated with consideration of the wheel-rail contact and self-guiding mechanisms. The results of this simulation confirmed the need for a robust steering control system to ensure proper vehicle functionality. The hybrid steering control system, which integrates a fuzzy logic controller with the self-guiding capability of the wheelset, demonstrated the ability to maintain the vehicle's equilibrium at the centerline of the track during operation. Simulation results showed that the system effectively reduces lateral deviations, keeping the vehicle stable with deviations below 10%, even under varying working conditions. This performance highlights the system's ability to leverage natural self-guiding forces while enhancing response and stability through active control.  
This study introduced a novel set of vehicle motion equations that integrate the self-guidance properties of the wheelset with an adaptive fuzzy logic controller. Simulations and comparative analysis confirmed that our approach improves positioning accuracy, reduces computational time, and enhances dynamic stability. These advancements contribute to the development of more efficient and precise autonomous railway inspection vehicles. Future work will focus on experimental validation and further optimization for diverse operational conditions.  
In future work, we plan to apply and experiment with this hybrid steering control system to a real model of the new micro-autonomous railway inspection vehicle to analyze and evaluate the system's energy efficiency and performance and improve its control. While the hybrid steering control system enhances lateral stability, several challenges  
Figure 14: Lateral displacement of the vehicle center running on a right-cornering track with hybrid steering control.  
remain for real-world implementation. High computational demands may affect onboard processing efficiency, while rail contamination, such as dust or oil, can alter wheel-rail adhesion, impacting control accuracy. Additionally, prolonged wheel wear may affect self-steering characteristics. Future work will focus on optimizing control algorithms, reducing computational load, and implementing adaptive tuning strategies to maintain performance under varying operational conditions.  
Investigation, supervision, conceptualization, and writing--review, YS.; implementation, methodology, data collection and writing, T.N.H.T.; All authors have read and agreed to the published version of the manuscript.  
This research is financially supported by the Ministry of Science and Technology, Taiwan (project number: MOST 110-2221-E-027-081).  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author(s).  
We thank the Ministry of Science and Technology, Taiwan, for supporting the project.  
The authors declare no conflicts of interest.