Robust Adaptive Cruise Control Design Using Model Predictive Control

This paper proposes a robust adaptive cruise control design based on Model Predictive Control (MPC) method, considering model uncertainties and external disturbances. Multiple model uncertainties, including uncertain environmental factors such as wind gusts and uncertainty in a power train system model, are characterized by a Linear Fractional Transform (LFT) method. Based on the LFT method, an upper bound of the error between the true uncertain system and the nominal prediction model is found based on linear matrix inequalities. Besides the model uncertainties mentioned above, the method considers an additive disturbance induced by modeling errors. A state observer simultaneously estimates the state and the additive disturbance within the control horizon to reduce the conservativeness of the error bound. Tightening constraints with the obtained error bound guarantees robust constraint satisfaction. Simulations performed on a CarSim-based high-fidelity vehicle model in a car-following scenario show that the proposed method can satisfy the constraints given in the MPC design in an uncertain environment with external disturbances.