MPC-Based Trajectory Tracking Control for Intelligent Vehicles State Key Lab of ASCL, Jilin University

Format:

Conference/Event

Author/Creator:

Ming, Ming, author.

Contributor:

Deng, Weiwen

Zhang, Sumin

Zhu, Bing

Conference Name:

SAE 2016 World Congress and Exhibition (2016-04-12 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2016

Summary:

AbstractIn this paper, a model predictive control (MPC) based trajectory tracking scheme utilizing steering wheel and braking or acceleration pedal is proposed for intelligent vehicles. The control objective is to track a desired trajectory which is obtained from the trajectory planner. The proposed control is based on a simplified third-order vehicle model, which consists of longitudinal vehicle dynamics along with a commonly used bicycle model. A nonlinear model predictive control (NMPC) is adopted in order to follow a given path by controlling front steering, braking and traction, while fulfilling various physical and design constraints. In order to reduce the computational burden, the NMPC is converted to a linear time-varying (LTV) MPC based on successive online linearization of the nonlinear system model. Two different test conditions have been used to verify the effectiveness of the proposed approaches through simulations using Matlab and CarSim. The results show that the desired speed and path are well tracked

Notes:

Vendor supplied data

Publisher Number:

2016-01-0452

Access Restriction:

Restricted for use by site license