Title :
Robust nonlinear predictive control for semiautonomous ground vehicles
Author :
Yiqi Gao ; Gray, Alison ; Carvalho, Adriano ; Tseng, H. Eric ; Borrelli, Francesco
Author_Institution :
Dept. of Mech. Eng., UC Berkeley, Berkeley, CA, USA
Abstract :
This paper presents a robust control framework for lane-keeping and obstacle avoidance of semiautonomous ground vehicles. It presents a systematic way of enforcing robustness during the MPC design stage. A robust nonlinear Model Predictive Controller (RNMPC) is used to help the driver avoid obstacles and track the road center line. A force-input nonlinear bicycle vehicle model is developed for the RNMPC control design. A robust invariant set is used in the RNMPC design to ensure robust satisfaction of state and input constraints in the presence of disturbances and model errors. Simulations and experiments on testing vehicles show the effectiveness of the proposed framework.
Keywords :
automatic guided vehicles; collision avoidance; nonlinear control systems; predictive control; robust control; MPC design stage; RNMPC control design; RNMPC design; force-input nonlinear bicycle vehicle model; lane keeping; obstacle avoidance; road center line; robust control framework; robust invariant set; robust nonlinear model predictive controller; robust nonlinear predictive control; robust satisfaction; robustness; semiautonomous ground vehicles; Computational modeling; Roads; Robustness; Safety; Tires; Trajectory; Vehicles; active safety; autonomous vehicles; robust control; robust nonlinear MPC; uncertain dynamics; vehicle safety;
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
Print_ISBN :
978-1-4799-3272-6
DOI :
10.1109/ACC.2014.6859253