Abstract
In this paper, a combined kinematic/torque output feedback control law is developed for leader follower-Based formation control using backstepping to accommodate the dynamics of the robots and the formation in contrast with kinematic-Based formation controllers. a neural network (NN) is introduced to approximate the dynamics of the follower and its leader using online weight tuning. Furthermore, a novel NN observer is designed to estimate the linear and angular velocities of both the follower robot and its leader. It is shown, by using the Lyapunov theory, that the errors for the entire formation are uniformly ultimately bounded while relaxing the separation principle. in addition, the stability of the formation in the presence of obstacles, is examined using Lyapunov methods, and by treating other robots in the formation as obstacles, collisions within the formation are prevented. Numerical results are provided to verify the theoretical conjectures. © 2006 IEEE.
Recommended Citation
T. Dierks and S. Jagannathan, "Neural Network Output Feedback Control of Robot Formations," IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 40, no. 2, pp. 383 - 399, article no. 5191113, Institute of Electrical and Electronics Engineers, Apr 2010.
The definitive version is available at https://doi.org/10.1109/TSMCB.2009.2025508
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Keywords and Phrases
Backstepping control; Formation control; Lyapunov stability; Obstacle avoidance; Output feedback
International Standard Serial Number (ISSN)
1083-4419
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Apr 2010
PubMed ID
19661005
Comments
National Science Foundation, Grant 0621924