Paper Info
Title
Event Triggered Distributed Adaptive Consensus Control For High-Order Nonlinear Multi-Agent Systems In Presence Of System Uncertainties
Abstract
In this paper, a novel event-triggered distributed adaptive consensus control strategy has been developed for high-order nonlinear multi-agent systems (MAS) with uncertain system dynamics. Compared with most existing results, proposed approach contributes on two main aspects, i.e. 1) distributed event-triggered control has been developed for a more general high-order nonlinear MAS, and 2) The impacts from practical imperfections, e.g. system uncertainties, have been considered. Firstly, the system uncertainties arc considered as bounded with a given upper bound. Through incorporating the upper bound of system uncertainties, a novel distributed event-triggered condition has been developed that can maintain the consensus of uncertain nonlinear MAS. Then, the system uncertainties are considered as unknown completely. A novel event-triggered distributed adaptive consensus control has been developed. For handling the unknown system dynamics, a series of novel distributed adaptive estimators have been designed to learn the system dynamics by using measured system data. Then, using the learnt system, the distributed event-triggered condition can be attained. Lyapunov stability analysis have been adopted to demonstrate the stability of developed novel event-triggered distributed consensus control. Eventually, simulation results are provided to verily the effectiveness of proposed designs.
Year
Venue
Field
2017
2017 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (RCAR)
Consensus,Nonlinear system,Upper and lower bounds,Control theory,Computer science,Lyapunov stability,Multi-agent system,System dynamics,Control system,Bounded function
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Sanket Chandan Lokhande100.34
Hao Xu21212.74
Harinder Singh Toor300.34