Article ID Journal Published Year Pages File Type
4946987 Neurocomputing 2017 25 Pages PDF
Abstract
The sampled-data cluster formation is proposed and considered for nonlinear multi-agent systems. The cluster formation problem, which is try to make all the agents divided into separated groups and each of the group realize distinct complement formation. Formation control protocol is constructed based on the event-triggered sampled-data method. Since the event condition for each agent is designed by using its own sampling information and latest transmitted information of its neighbors, the event condition can be intermittently examined at constant sampling instants. A sufficient condition is given to solve the cluster formation problem for fixed and switching topologies. Finally, the effectiveness of the control mechanism is demonstrated by numerical examples.
Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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