Practical Nonlinear Model Predictive Controller Design for Trajectory Tracking of Unmanned Vehicles

被引:5
|
作者
Pang, Hui [1 ]
Liu, Minhao [1 ]
Hu, Chuan [2 ]
Liu, Nan [1 ]
机构
[1] Xian Univ Technol, Sch Mech & Precis Instrument Engn, Xian 710048, Peoples R China
[2] Univ Alaska Fairbanks, Dept Mech Engn, Fairbanks, AK 99775 USA
基金
中国国家自然科学基金;
关键词
unmanned vehicle; nonlinear model prediction controller; trajectory tracking; outdoor field test; AUTONOMOUS VEHICLES; PATH TRACKING; OPTIMIZATION;
D O I
10.3390/electronics11071110
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The trajectory tracking issue of unmanned vehicles has attracted much attention recently, with the rapid development and implementation of sensing, communication, and computing technologies. This paper proposes a nonlinear model predictive controller (NMPC) for the trajectory tracking application of an unmanned vehicle (UV). First, a two-degree-of-freedom (2-DOF) kinematics model of this UV is used to derive the desirable controller with two control variables as forward velocity and yaw angle. Next, the one-step Euler method is employed to establish the nonlinear prediction model, then a nonlinear optimization objective function is formulated to minimize the tracking errors of forward velocity and yaw angle from a preset time-varying reference road. Finally, the effectiveness of the proposed NMPC scheme is assessed under two different driving scenarios via MATLAB simulations. The simulation results confirm that the proposed NMPC scheme reveals better control accuracy and computational efficiency than the standard MPC controller under two different prescribed roads. Moreover, an outdoor field test is conducted to verify the performance of the proposed NMPC scheme, and the results show that the proposed NMPC can be applied to the real vehicle and can improve the tracking accuracy and the driving stability of trajectory tracking.
引用
收藏
页数:18
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