Model-Based Yaw-Rate Tracking Control with Online Adaptation of Steering and Tire Parameters for an E-Corner-Based Four-Wheel Independent Steering Vehicle

Yun-m Sung; Jae-poong Lee; Jung-min Cho

doi:10.22680/kasa2026.18.1.110

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Model-Based Yaw-Rate Tracking Control with Online Adaptation of Steering and Tire Parameters for an E-Corner-Based Four-Wheel Independent Steering Vehicle

31 March 2026. pp. 110-126

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Abstract

This paper presents a model-based yaw-rate tracking control framework for an e-corner–based vehicle with four-wheel independent steering (4WIS). Owing to the over-actuated nature of the platform, accurate yaw-motion generation requires a consistent connection among vehicle yaw dynamics, tire lateral-force generation, and steering actuator dynamics. A hierarchical feedforward framework is developed to map a desired yaw-rate profile to the required yaw moment, allocate it to per-wheel lateral-force commands, and convert them into per-wheel steering angle and steering motor torque commands via an inverse actuator model. While feedforward control provides fast response and physical interpretability, its performance can degrade under steering actuator uncertainties, tire-parameter variations, and unmodeled disturbances.

To mitigate these effects without introducing overly complex robust-control structures, a recursive least-squares (RLS)–based parameter adaptation scheme is integrated into the feedforward pipeline. The proposed method estimates and updates the key model parameters—namely the steering actuator viscous damping and the tire cornering stiffness—from input–output data, and uses the updated parameters to align the feedforward torque/steering command generation with the actual vehicle response. The proposed approach is evaluated in simulation under a deliberate 10% mismatch in the viscous damping and cornering stiffness parameters. Comparative studies are conducted for four configurations: feedforward only, feedforward with yaw-rate feedback, feedforward with RLS adaptation, and feedforward with both RLS adaptation and feedback. The results show that RLS-based adaptation improves yaw-rate tracking robustness under parameter uncertainty and reduces reliance on feedback compensation, achieving stable tracking performance across uncertainty scenarios.

Keywords

Vehicle dynamics

e-Corner system

Yaw-rate tracking

Model-based feedforward

Recursive least squares

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Information

Publisher :Korean Auto-vehicle Safety Association
Publisher(Ko) :한국자동차모빌리티안전학회
Journal Title :Journal of Auto-vehicle Safety Association
Journal Title(Ko) :자동차안전학회지
Volume : 18
No :1
Pages :110-126
Received Date : 2026-01-19
Revised Date : 2026-02-09
Accepted Date : 2026-02-11
DOI :https://doi.org/10.22680/kasa2026.18.1.110

Journal of Auto-vehicle Safety Association ISSN:2005-9396(Print) 자동차안전학회지

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