Model predictive control for trajectory-tracking and formation of wheeled mobile robots

被引:15
|
作者
Wei, Juntao [1 ]
Zhu, Bing [1 ]
机构
[1] Beihang Univ, Res Div 7, Beijing 100191, Peoples R China
来源
NEURAL COMPUTING & APPLICATIONS | 2022年 / 34卷 / 19期
基金
中国国家自然科学基金;
关键词
Model predictive control; Trajectory tracking; Formation control; Non-holonomic systems; SYSTEMS;
D O I
10.1007/s00521-022-07195-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Model predictive control (MPC) naturally guarantees optimal transient process and constraints satisfaction. Most mature MPC theories concern with linear time-invariant systems, it is not trivial to develop MPC for time-varying or nonlinear systems. A linear time-varying model predictive control strategy is proposed in this paper for single-wheeled mobile robot trajectory tracking subject to the non-holonomic constraint and control constraints. The kinematic equation of the robot is converted into a linear time-varying form after linearizing and discretizing, the time-varying MPC is capable to be applied in consequence. The proposed trajectory tracking task is extended to the formation control among multiple robots solved by means of nonlinear model predictive control directly. The extended formation MPC is in the leader-following framework. Recursive feasibility and stability are proved for the closed-loop system.
引用
收藏
页码:16351 / 16365
页数:15
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