Paper Info
Title
Neural network-based adaptive optimal consensus control of leaderless networked mobile robots
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.
Year
DOI
Venue
2014
10.1109/ADPRL.2014.7010648
Adaptive Dynamic Programming and Reinforcement Learning
Keywords
Field
DocType
Lyapunov methods,adaptive control,mobile robots,multi-robot systems,neurocontrollers,optimal control,robot dynamics,stability,vectors,Lyapunov stability theorem,NN weight tuning laws,approximated value function,augmented error vector function,consensus-based formation errors,identified formation dynamics,leaderless networked mobile robots,neural network-based adaptive optimal consensus control,unknown robot dynamics,Adaptive control,consensus,formation control,mobile robots,neural networks,optimal control,uncertain dynamics
Control theory,Optimal control,Control theory,Computer science,Lyapunov stability,Bellman equation,Adaptive control,Robot,Artificial neural network,Mobile robot
Conference
Citations 
PageRank 
References 
0
0.34
9
Authors
3
Name
Order
Citations
PageRank
Haci Mehmet Guzey160.86
Hao Xu221414.63
Sarangapani Jagannathan3113694.89