@article{ref1,
title="Adaptive model predictive fault-tolerant control for four-wheel independent steering vehicles with sensitivity estimation",
journal="International journal of automotive technology",
year="2023",
author="Oh, Se Chan and Song, Tae Jun and Kim, Min Jun and Oh, Kwang Seok",
volume="24",
number="3",
pages="829-850",
abstract="This paper presents an adaptive model predictive fault-tolerant control (FTC) algorithm based on sensitivity estimation and exponential forgetting-based recursive least squares (RLS) for four-wheel independent steering vehicles. The model predictive control algorithm was designed according to physical constraints for four-wheel independent steering control with adaptive integral action. To improve the control performance in transient and steady-state regions, sensitivity-based adaptive rules for the weighting factor of the model predictive controller and integral gain were developed using the gradient descent method. The sensitivity was defined by a virtual relationship function and was estimated using RLS with a forgetting factor. Additionally, a FTC strategy with the equality constraint was proposed for enhancing the yaw-rate tracking control performance despite the existence of faults in the steering system. The proposed fault-tolerant steering control algorithm was developed in a MATLAB/Simulink environment, and its performance was evaluated via co-simulation in the MATLAB/Simulink and CarMaker software programs under various evaluation scenarios.<p /> <p>Language: en</p>",
language="en",
issn="1229-9138",
doi="10.1007/s12239-023-0068-8",
url="http://dx.doi.org/10.1007/s12239-023-0068-8"
}