Intelligent Vehicle Path Tracking and Stability Cooperative Control Strategy Based on Stable Domain

Abstract

<div>Vehicle path tracking and stability management are critical technologies for intelligent driving. However, their controls are mutually constrained. This article proposes a cooperative control strategy for intelligent vehicle path tracking and stability, based on the stable domain. First, using the vehicle’s two-degrees-of-freedom (DOF) model and the Dugoff tire model, a phase plane representation is constructed for the vehicle’s sideslip angle and sideslip angular velocity. An enhanced method utilizing five eigenvalues is employed to partition the vehicle stability domain. Second, by employing the divided vehicle stable domain, the design of a fuzzy controller utilizes the Takagi–Sugeno (TS) methodology to determine the weight matrix gain for path tracking and stability control. Subsequently, a fuzzy model predictive control (TS-MPC) cooperative control strategy is designed, which takes into account both the precision of path tracking and the stability of the vehicle. Finally, a simulation test and comparative analysis with a generic MPC controller were conducted. The findings indicate that compared to the generic MPC cooperative controller, the control strategy designed in this article markedly enhances the stability of the vehicle and boosts the accuracy of path tracking.</div>