A Novel Adaptive Steering Torque Control Approach for Human–Machine Cooperation Autonomous Vehicles
Jian Wu, Junda Zhang, Yang Tian, Liang Li
Abstract
Human–machine cooperation (HMC) driving can realize the sharing of vehicle control rights between drivers and autonomous driving systems. However, the system disturbances and parameter uncertainties introduced by HMC driving are also inevitable. To solve the above problems, this study proposes an HMC steering torque control method based on the model reference adaptive control (MRAC). First, to describe the driver’s operating behavior and the transient characteristics of the steering system and the vehicle, an HMC vehicle-road model with steering torque input is established. Then, the exponential decay function is taken as a reference model to increase the decay rate of road lateral deviation. Besides, for the problem of model parameter uncertainties, the parameter adaptive laws are designed in the control process, and the robust term is considered into the parameter adaption law to improve the robustness of the closed-loop system. Robust stability under bounded disturbances is guaranteed by boundary estimation of unknown disturbances between driver input and steering load. Finally, simulations and experiments are carried out to verify the proposed control strategy. The results demonstrate that the proposed control strategy can converge rapidly under the disturbances and parameter uncertainties introduced by HMC.