Abstract
A novel neural network (NN)-based optimal adaptive consensus control scheme is introduced in this paper for networked mobile robots in the presence of unknown robot dynamics. Throughout the paper, two NNs are used. The unknown formation dynamics of each robot is identified by using the first NN. The second NN is utilized to approximate a novel value function derived in this paper as a function of augmented error vector, which is comprised of the regulation and consensus-based formation errors of each robot. A novel near optimal controller is developed by using approximated value function and identified formation dynamics. The Lyapunov stability theorem is employed to derive the NN weight tuning laws and demonstrate the consensus achievement of the overall formation. The simulation results are depicted to show performance of our theoretical claims.
Recommended Citation
H. M. Guzey et al., "Neural Network-Based Adaptive Optimal Consensus Control of Leaderless Networked Mobile Robots," IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - ADPRL 2014: 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, Proceedings, article no. 7010648, Institute of Electrical and Electronics Engineers, Jan 2014.
The definitive version is available at https://doi.org/10.1109/ADPRL.2014.7010648
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Keywords and Phrases
Adaptive control; consensus; formation control; mobile robots; neural networks; optimal control; uncertain dynamics
International Standard Book Number (ISBN)
978-147994553-5
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
14 Jan 2014
