Robust Model Predictive Control for Adaptive Cruise Control with Model Uncertainties

초록

This paper proposes a tube-based Model Predictive Control (MPC) method for Adaptive Cruise Control (ACC), where model uncertainty and external disturbances are considered. The model uncertainty is described as an inequality based on a Linear Fractional Transform (LFT) method. The inequality is used to generate a scalar system to bound the model error between the nominal prediction model and the uncertain system with the existence of external disturbances. Robust constraint satisfaction is then guaranteed by tightening the constraints by a tube with the size of the upper bound of the model error. Simulations are performed on a CarSim-based high-fidelity vehicle model in a car-following scenario. The proposed method shows its ability to satisfy the constraints given in the MPC design, even in the presence of modeling and communication errors.

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