In this paper,the problem of second–order consensus in multi-agent systems with sampled position data is handled. Due to the discrete nature of the information transmission among agents,there is an increasing interest in such kind of systems. By thinking of collecting sampled position data in a certain time interval,that is more general than considering just the sampling period as in many papers,the velocity is here approximated through fuzzy transform (or F–trasform for short). F–transform was proved to have high accuracy,even when data are not correlated,and a low computational cost. This approximation changes the autonomous system herein considered in a nonautonomous one. In light of this,we formally discuss the conditions under which a quasi–consensus can be achieved. Finally,simulation examples are given to verify and illustrate the theoretical achievements.
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