Abstract
This paper aims to develop a Global Chassis Controller to coordinate the Active Front steering, Direct Yaw Control and Active Suspension controllers, in the ambition to improve the overall vehicle performance. A multilayer control architecture is adopted. It contains a local control layer and a decision layer. The local objectives for the sub-controllers in the control layer concern explicitly: maneuverability, lateral stability, rollover avoidance, and ride comfort. The sub-controllers are designed based on the super-twisting sliding mode theory. The decision layer is developed to promote/attenuate the local objectives of the sub-controllers, in order to remove the conflicts among the different objectives and extract the maximum benefit from the coordination using some evaluation criteria. This layer monitors the dynamics of the vehicle, calculates and sends scheduled gains to the sub-controllers, based on fuzzy logic rules and a stability criterion. Finally, the proposed Global Chassis Controller is validated on Matlab/Simulink using a vehicle model validated on the professional vehicle simulator “SCANeR Studio”. The results show the effectiveness of the proposed strategy.
Highlights
Development of a decision layer that promotes/attenuates the local sub-controllers objectives. This layer monitors the dynamics of the vehicle, calculates and sends scheduled gains to the sub-controllers, based on fuzzy logic rules and a stability criterion
The objective of the AFS is to converge the measured yaw rate ψwhose dynamics is described in (5) to the saturated reference ψre f, to enhance the maneuverability in the framework of the lateral stability. This can be done by adjusting the driver steering angle δd through the introduction of the corrective term δc as the AFS control input calculated based on the super-twisting Sliding Mode control theory. δd and Cz are treated as exogenous inputs to the yaw dynamics of (5)
The results show that the LTR is the best when the GCC strategy is adopted compared to other strategies
Summary
Development of a decision layer that promotes/attenuates the local sub-controllers objectives. Observed, e.g., the DYC will be less solicited, the vehicle speed will less drop, and others... This layer monitors the dynamics of the vehicle, calculates and sends scheduled gains to the sub-controllers, based on fuzzy logic rules and a stability criterion. The paper structure is as follows: Section 2 develops the GCC system, starting by a review of the vehicle model, passing by the development of the sub-controllers to realize their local objectives and analyze the interactions between them, to develop the decision layer.
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