| ADAPTIVE MODEL PREDICTIVE FAULT-TOLERANT CONTROL FOR
FOUR-WHEEL INDEPENDENT STEERING VEHICLES WITH
SENSITIVITY ESTIMATION |
| Se Chan Oh 1, Tae Jun Song 1, Min Jun Kim 2, Kwang Seok Oh 1 |
1School of ICT, Robotics & Mechanical Engineering, Hankyong National University
2Hyundai Motor Company, Institute of Advanced Technology Development |
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| ABSTRACT |
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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. |
| Key Words:
Model predictive control, Four-wheel independent steering, Adaptive rule, Sensitivity, Gradient descent
method, Recursive least squares, Forgetting factor |
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Corresponding Author.
Kwang Seok Oh , Email. 
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