TY - GEN
T1 - Optimal Path Tracking Controller of Multiple Unmanned Tracked Vehicles
T2 - 7th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2022
AU - Zang, Zheng
AU - Li, Zhiwei
AU - Gong, Jianwei
AU - Gong, Cheng
AU - Yu, Huilong
AU - Zhang, Xi
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In this paper, we propose a novel distributed model predictive control (DMPC) approach for optimal path tracking (OPT) in multiple unmanned tracked vehicles (UTVs). The novelty of this work lies in the integration of longitudinal and lateral motion control by minimizing the cost function and formulating a standard multi-objective DMPC optimization problem. Firstly, a longitudinal and lateral coupled kinematic model of the tracked vehicle is established. And then a DMPC approach considering multi-objective optimization is formulated to deal with multiple tracked vehicle path tracking control and distributed computing problems. Some challenging scenarios including S-bend and rectangle are tested and validated in simulation and real tracked vehicle for the proposed OPT strategy. A comparison is made between distributed and centralized methods, and the comparison result shows the rapidity of DMPC approach.
AB - In this paper, we propose a novel distributed model predictive control (DMPC) approach for optimal path tracking (OPT) in multiple unmanned tracked vehicles (UTVs). The novelty of this work lies in the integration of longitudinal and lateral motion control by minimizing the cost function and formulating a standard multi-objective DMPC optimization problem. Firstly, a longitudinal and lateral coupled kinematic model of the tracked vehicle is established. And then a DMPC approach considering multi-objective optimization is formulated to deal with multiple tracked vehicle path tracking control and distributed computing problems. Some challenging scenarios including S-bend and rectangle are tested and validated in simulation and real tracked vehicle for the proposed OPT strategy. A comparison is made between distributed and centralized methods, and the comparison result shows the rapidity of DMPC approach.
UR - http://www.scopus.com/inward/record.url?scp=85143674701&partnerID=8YFLogxK
U2 - 10.1109/ICARM54641.2022.9959135
DO - 10.1109/ICARM54641.2022.9959135
M3 - Conference contribution
AN - SCOPUS:85143674701
T3 - ICARM 2022 - 2022 7th IEEE International Conference on Advanced Robotics and Mechatronics
SP - 581
EP - 586
BT - ICARM 2022 - 2022 7th IEEE International Conference on Advanced Robotics and Mechatronics
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 9 July 2022 through 11 July 2022
ER -