TY - GEN
T1 - Fast Source Seeking with Obstacle Avoidance via Extremum Seeking Control
AU - Xu, Tianlai
AU - Chen, Guodong
AU - Zhou, Guoqing
AU - Liu, Ziang
AU - Zhang, Zexu
AU - Yuan, Shuai
N1 - Publisher Copyright:
© 2022 ACA.
PY - 2022
Y1 - 2022
N2 - Navigation tasks often need explicit unknown information. However, when the positioning information is unavailable and the target location is unknown, this task can be transformed into a source seeking problem. In this paper, the source potential field and artificial potential field are combined into a navigation function, and the normalized extremum seeking is used to realize the source seeking task of a unicycle with convex obstacles in unknown environment. Firstly, the kinematics of the unicycle is modeled, and the Rimon-Koditschek navigation function of the unicycle is established by combining source potential field and artificial potential field. Then a unicycle source finding system based on normalized extremum seeking is built and Lie bracket system is used to approximate the system, and the stability of the system is proved by Lyapunov stability criterion. Finally, simulation results show that normalized extremum seeking has better robustness and better transient and steady-state performance than general extremum seeking for source seeking system. The navigation function using normalized extremum seeking can generate a collision-free navigation trajectory faster in the environment with obstacles.
AB - Navigation tasks often need explicit unknown information. However, when the positioning information is unavailable and the target location is unknown, this task can be transformed into a source seeking problem. In this paper, the source potential field and artificial potential field are combined into a navigation function, and the normalized extremum seeking is used to realize the source seeking task of a unicycle with convex obstacles in unknown environment. Firstly, the kinematics of the unicycle is modeled, and the Rimon-Koditschek navigation function of the unicycle is established by combining source potential field and artificial potential field. Then a unicycle source finding system based on normalized extremum seeking is built and Lie bracket system is used to approximate the system, and the stability of the system is proved by Lyapunov stability criterion. Finally, simulation results show that normalized extremum seeking has better robustness and better transient and steady-state performance than general extremum seeking for source seeking system. The navigation function using normalized extremum seeking can generate a collision-free navigation trajectory faster in the environment with obstacles.
KW - Normalized extremum seeking
KW - artificial potential field
KW - navigation function
KW - source seeking
UR - https://www.scopus.com/pages/publications/85135612550
U2 - 10.23919/ASCC56756.2022.9828209
DO - 10.23919/ASCC56756.2022.9828209
M3 - 会议稿件
AN - SCOPUS:85135612550
T3 - ASCC 2022 - 2022 13th Asian Control Conference, Proceedings
SP - 2097
EP - 2102
BT - ASCC 2022 - 2022 13th Asian Control Conference, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th Asian Control Conference, ASCC 2022
Y2 - 4 May 2022 through 7 May 2022
ER -