Path tracking control strategy for the intelligent vehicle considering tire nonlinear cornering characteristics in the PWA form. Issue 6 (April 2022)

• Record Type: Journal Article
• Authors: Sun, Xiaoqiang; Wang, Yulin; Hu, Weiwei; Cai, Yingfeng; Huang, Chen; Chen, Long
• Is Part Of: Journal of the Franklin Institute. Volume 359:Issue 6(2022)
• Page Start: 2487
• Page End: 2513
• Publication Date: 2022-04
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2022.02.001
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: To improve the path tracking control performance of the intelligent vehicle under critical maneuvers, a novel control strategy is introduced in this work. Considering that the tire cornering characteristics show high nonlinearities and uncertainties under those special driving conditions, a three-dimensional piecewise affine (PWA) identification method is proposed to realize the nonlinear modeling of the tire cornering characteristics for the first time. On this basis, the PWA model of the vehicle lateral dynamics is established. To obtain the vehicle target yaw rate for path tracking, a driver direction control model with adaptive preview time is put forward. Then, the linear quadratic optimal control method is further adopted to design multiple path tracking controllers for different working areas of the affine subsystems, thus the optimal steering angles of the front wheels can be generated to guarantee the path tracking performance for the intelligent vehicle under a wide range of driving conditions. Finally, to evaluate the performance of the proposed path tracking control strategy which considers the tire nonlinear cornering characteristics in the PWA form, the CarSim-Simulink co-simulation work is conducted. The co-simulation results show that the proposed control strategy presents significant performance advantages over the other two methodologies and demonstrates satisfactory path tracking control performance.