高技术通讯2024，Vol.34Issue(3)：275-281,7.DOI:10.3772/j.issn.1002-0470.2024.03.006
基于紧约束鲁棒模型预测控制的无人车辆轨迹跟踪控制
Trajectory tracking control of unmanned vehicles based on tight constrained robust model predictive control
摘要
Abstract
A tight constrained robust model predictive control(MPC)method is proposed for unmanned vehicles to track trajectory based on the nonlinear dynamics model of the vehicle.Firstly,a linear discrete error model of the vehicle with bounded disturbances is constructed by using the magic formula tire model and the vehicle 3-degree of freedom system.Secondly,a tight constraint control strategy is used to design the robust optimization problem of the system.Lastly,the optimal control sequence is obtained through on-line optimization,and the feasible control sequence that satisfies the constraint conditions at multiple times is constructed off-line.Simulation results show that the proposed algorithm can make the vehicle track the reference trajectory stably and quickly,and effectively improve the utiliza-tion of system computing resources.关键词
模型预测控制(MPC)/紧约束/无人车/轨迹跟踪Key words
modelpredictivecontrol(MPC)/tightconstraint/unmannedvehicle/trajectorytracking引用本文复制引用
贾立新,林秀锐,倪洪杰,刘安东..基于紧约束鲁棒模型预测控制的无人车辆轨迹跟踪控制[J].高技术通讯,2024,34(3):275-281,7.基金项目
国家自然科学基金(61973275)项目资助. （61973275）
