Adaptive Sliding Mode Tracking Algorithm for Heavy-Haul Trains Under Actuator Saturation Constraints

Title

Adaptive Sliding Mode Tracking Algorithm for Heavy-Haul Trains Under Actuator Saturation Constraints

Author

1. Preeti Patel, Student, Saveetha Engineering College (Autonomous), Tamil Nadu, India
2. Saravanan M.P., Professor, Saveetha Engineering College (Autonomous), Tamil Nadu, India

Abstract

Heavy-haul trains require exact control mechanisms to ensure safety, stability, and efficiency. However, when actuators reach their saturation limits, the control system's performance can degrade, leading to instability and tracking errors. In this paper, we propose an adaptive sliding mode tracking algorithm designed to handle the effects of actuator saturation. The algorithm dynamically adjusts control inputs to maintain stability, minimize tracking errors, and improve robustness against external disturbances. We demonstrate the algorithm's effectiveness in various actuator saturation scenarios through simulations.

Keywords

Conclusion

This paper presented an adaptive sliding mode tracking algorithm to address actuator saturation in heavy-haul trains. The proposed method dynamically adjusts the control input based on the saturation level, ensuring robust tracking performance and system stability under varying operating conditions. The simulation results verify that the algorithm outperforms conventional SMC and adaptive control strategies in terms of both accuracy and robustness. Future work will focus on experimental validation and real-time implementation in heavy-haul train systems.

Author Contrubution

The author handled all aspects of the study, including its design, data collection, analysis, and manuscript preparation.

Funding

This work did not receive any specific grant from funding agencies in the public, commercial, or non-profit sectors for its research, authorship, or publication.

Conflict of Interest

There are no conflicts of interest to report from any of the authors.

Data Sharing Statement

Data sharing is not relevant to this study.

Software And Tools Use

There is no software or tools usage information relevant to this research.

Acknowledgements

I acknowledge the support and expertise of those who helped with this research and manuscript, and thank the peer reviewers for their valuable insights.