Open AccessAnti‐sideslip path tracking of wheeled mobile robots based on fuzzy model predictive control
Author(s) -
Bai Guoxing,
Meng Yu,
Liu Li,
Luo Weidong,
Gu Qing,
Li Kailun
Publication year - 2020
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2019.4019
Subject(s) - robustness (evolution) , control theory (sociology) , model predictive control , mobile robot , fuzzy logic , robot , fuzzy control system , computer science , control engineering , engineering , control (management) , artificial intelligence , biochemistry , chemistry , gene
When a wheeled mobile robot is travelling at high longitudinal velocities and turning, it may sideslip. Except for a few researchers, this issue has not received much attention. However, there is a high possibility that sideslip may cause danger, so the authors think this problem needs to be solved urgently. The mechanism of preventing sideslip is simple, which is to reduce the longitudinal velocity of the robot when turning. But, how to slow down is a question worth studying. To this end, they have proposed two schemes, but these two schemes have poor real‐time performance and poor robustness to positioning errors, respectively. In order to solve the above problems, considering that the real‐time and robustness of fuzzy control are very good, they propose a controller by combining robust control and model predictive control in this Letter. The fuzzy control is used to adjust the longitudinal velocity according to the state of the robot, and the model predictive control is used to achieve path tracking. According to the simulation results, the proposed fuzzy model predictive controller does have small errors, small sideslip, good real‐time performance, and good robustness to positioning errors.