Adaptive Sliding Mode Control of Rack Position Tracking System for Steer-by-Wire Vehicles

Kim, Kwangil; Lee, Jaepoong; Kim, Minjun; Yi, Kyongsu · 2020 · OpenAlex-citations

DOI: 10.1109/access.2020.3021038

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This paper addresses the challenge of ensuring precise rack position tracking in steer-by-wire (SBW) vehicles across diverse driving conditions, including varying road surfaces and zero vehicle speeds. SBW systems eliminate mechanical linkages between the steering wheel and front wheels, offering improved stability and maneuverability but requiring robust control algorithms to handle uncertainties. Existing methods often rely on estimating tire cornering stiffness or using complex models that are difficult to implement in real-time or fail at low speeds. The authors propose an adaptive sliding mode control (ASMC) algorithm that utilizes only motor position sensors, eliminating the need for tire/road friction information or cornering stiffness estimation. The methodology involves developing a stiffness parameter adaptation law to compensate for disturbances in the SBW rack system. The dynamic model replaces the self-aligning torque with a stiffness model, where the stiffness coefficient is adjusted via an adaptation law to handle various road conditions without requiring gain tuning. Additionally, a dynamic stiffness model is introduced to address tracking performance at zero vehicle speed, a scenario where traditional models fail due to division by zero in slip angle calculations. This model features a variable stiffness center that changes based on the actual rack position, accounting for the elastic equilibrium point observed during parking maneuvers. The control strategy combines an equivalent control input with a switching control input to ensure asymptotic stability, proven via Lyapunov analysis. The study validates the proposed algorithm through computer simulations and vehicle tests under dry asphalt, wet road conditions, and zero-speed scenarios. Results demonstrate that the ASMC algorithm effectively guarantees rack position tracking performance without additional gain tuning. Specifically, the adaptation law successfully compensates for disturbances caused by varying road friction, while the dynamic stiffness model ensures accurate tracking during parking maneuvers where the vehicle speed is zero. The system maintains robustness against unstructured uncertainties and avoids the chattering phenomena associated with conventional sliding mode control. The significance of this work lies in its practical applicability for next-generation SBW systems. By removing the dependency on difficult-to-estimate tire parameters and providing a solution for low-speed tracking, the proposed control algorithm enhances the reliability and safety of SBW vehicles. The findings suggest that adaptive sliding mode control, combined with a dynamic stiffness model, offers a robust and implementable solution for maintaining steering precision in real-world driving situations, including critical low-speed operations like parking. This approach simplifies the control architecture by relying solely on readily available motor position sensors.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• steering pattern