Path tracking control of a four-wheel-independent-steering electric vehicle based on model predictive control

• Published in: Chinese Control Conference pp. 9360 - 9366
• Main Authors: Peng Hang, Fengmei Luo, Shude Fang, Xinbo Chen
• Format: Conference Proceeding
• Language: English
• Published: Technical Committee on Control Theory, CAA 01.07.2017
• Subjects: electric vehicle; Electric vehicles; four-wheel-independent-steering; Mathematical model; model predictive control; Numerical models; Optimization; path tracking; Robustness; Stability analysis; Tires
• ISSN: 1934-1768
• DOI: 10.23919/ChiCC.2017.8028849

Compared with the traditional front-wheel-steering (FWS) vehicles, four-wheel-independent-steering (4WIS) vehicles have better handling stability and path-tracking performance. In this paper, a novel 4WIS electric vehicle (EV) is proposed and it is viewed as a controlled object for path tracking. The nonlinear dynamical model of the 4WIS EV is built based on the nonlinear Dugoff tire model. For controller design, the nonlinear dynamical model is simplified as a linear model. Then, a linear model predictive controller (MPC) is designed for the 4WIS EV to follow reference path which is expressed as reference yaw angle and reference longitudinal displacement. The main objective of the MPC is to minimize the error between the reference signals and measurement signals. In the procedure of solving MPC, the constraints are taken into consideration including actuator constraints, tire slip angle constraints and the lateral acceleration constraint. To evaluate the performance of the designed controller, two simulation conditions are carried out using the nonlinear vehicle model with 9 degrees of freedom (DOF) in MATLAB/Simulink. Simulation results show that the designed MPC has good path-tracking performance and strong robust performance against parametric perturbations.