This study presents an attitude control system for a four-wheel steering vehicle had a driving support system (DSS). Generally, the DSS is not a suitable system to ensure stability of the four-wheel vehicles when the ...
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This study presents an attitude control system for a four-wheel steering vehicle had a driving support system (DSS). Generally, the DSS is not a suitable system to ensure stability of the four-wheel vehicles when the vehicles drive some slippery roads such as a snowy road. Therefore, in this study, we propose the attitude control system for the four-wheel steering vehicle which can ensure the stability. In addition, the four-wheel vehicle as control target has a function that handles a steering system of front and rear, independently. To design this control system, we use a state expressed disturbance distributed observer(DOB), discrete-time LQR and linear model predictive control(LMPC). Finally, we present good validation result from a movement-control simulation of the four-wheel steering vehicle.
In previous research, it has been found that linear model predictive control（LMPC） has advantages in dealing with system constraints, while preview control can introduce nonlinear feedforward information into path t...
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In previous research, it has been found that linear model predictive control（LMPC） has advantages in dealing with system constraints, while preview control can introduce nonlinear feedforward information into path tracking. But so far, the advantages of these two control methods have not been combined. For the combination of LMPC and preview control, the most important problem to be solved is how to set the preview distance. To solve this problem, we added different preview distances for the LMPC-based path tracking controller under different working conditions. Through the simulation results, we reached five conclusions. Firstly, the performance of LMPC can be improved by adding the preview distance. Secondly, for the LMPC-based path tracking controller, there is an optimal preview distance. Thirdly, the optimal preview distance is related to the longitudinal velocity, and usually, a longer preview distance should be taken when the longitudinal velocity is higher. Fourthly, the correlation between the curvature of the reference path and the optimal preview distance is weak. Fifthly, adjusting the preview distance does not affect the real-time performance of the LMPC controller.
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