| 제목 |
ADAPTIVE MODEL PREDICTIVE FAULT-TOLERANT CONTROL FOR FOUR-WHEEL INDEPENDENT STEERING VEHICLES WITH SENSITIVITY ESTIMATION
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| 분야 |
Body and Safety |
| 언어 |
English |
| 저자 |
Sechan Oh(Hankyong National University), TaeJun Song(Hankyong National University), Minjun Kim(Hyundai Motor Company), Kwang Seok Oh(Hankyong National University ) |
| Key Words |
Model predictive control, Four-wheel independent steering, Adaptive rule, Sensitivity, Gradient descent method, Recursive least squares, Forgetting factor |
| 초록 |
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.
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