An Innovative Robust $\mathcal{H}_{\infty}$ Adaptive Cruise Control Method with Input Constraint Considering Tire-road Friction Coefficient

Driving safety may be compromised by aggressive acceleration/deceleration that exceeds the road surface limit. This paper aims to address two problems: how to obtain the maximum acceleration constraint and how to adjust the control strategy accordingly. We first propose a kinematic information fusion method based on adaptive Kalman Filter (AKF) to obtain accurate velocity and acceleration, and then develop a tire-road friction coefficient (TRFC) estimation method based on quadratic programming (QP) to determine the maximum acceleration that the road can provide. After that, we establish a new robust
$\mathcal{H}_{\infty}$
design criterion with input constraint (RHIC), which ensures that the input of adaptive cruise control (ACC) system is constrained and the disturbance is attenuated. Finally, some experiments and simulations are presented to demonstrate the effectiveness of the proposed methods.