Path Tracking Control for Differential Steering Autonomous Vehicles with Active Body Inward Tilt

Considering the problems that the inner wheel load decreases due to centrifugal force during the steering of differential steering autonomous vehicles, which may result in differential steering failure or even vehicle rollover in severe cases, a path-tracking strategy for differential steering autonomous vehicles considering active body inward tilt is proposed. Aiming at the problems of fixed parameters and insufficient adaptability of model predictive control in the path-tracking process of autonomous vehicles, this paper proposes a collaborative adaptive model predictive controller (MPC) with preview time and weight matrix based on fuzzy inference as the upper control, so as to realize the tracking control of the reference path by conventionally steered autonomous vehicles. In the lower control, an H∞/H2 hybrid controller with particle swarm optimization (PSO)-based parameter self-tuning is employed to control the differential steering autonomous vehicle (DSAV) to track the reference model, achieving differential steering and active body inward tilt simultaneously. Co-simulation results of CarSim and Simulink show that the proposed method outperforms the fixed-preview-time MPC and the manually tuned H∞/H2 hybrid controller. Compared with the latter, the maximum absolute values of lateral deviation and yaw angle deviation are reduced by 17.9% and 14.5%, respectively; the maximum deviation in the reference yaw rate is decreased by 21.2%; the maximum absolute value of the inward tilt angle is reduced by 53.4%; and the maximum values of LTR and occupant-perceived lateral acceleration are lowered by 57.1% and 44.2%, respectively.