In this paper, the consensus problem with position sampled data for second-order multi-agent systems is investigated. The interaction topology among the agents is depicted by a directed graph. The full-order and reduced-order observers with position sampled data are proposed, by which two kinds of sampled data-based consensus protocols are constructed. With the provided sampled protocols, the consensus convergence analysis of a continuous-time multi-agent system is equivalently transformed into that of a discrete-time system. Then, by using matrix theory and a sampled control analysis method, some sufficient and necessary consensus conditions based on the coupling parameters, spectrum of the Laplacian matrix and sampling period are obtained. While the sampling period tends to zero, our established necessary and sufficient conditions are degenerated to the continuous-time protocol case, which are consistent with the existing result for the continuous-time case. Finally, the effectiveness of our established results is illustrated by a simple simulation example.
Ontology is increasingly being used to build applications that utilize domain-specific knowledge. How to process ontology-based query efficiently has received many attentions in resent research. The measurement of concept's similarity is basis and foundation of semantic query based on ontology, however, current similarity measurement of ontology concepts involves in artificial intelligence area and psychological area limit efficiency when facing the application that the information is complicated, we propose a model to measure the semantic similarity between concepts on the basis of psychological studies about similarity and artificial intelligence studies about similarity, we express how to implement semantic query. Our approach enables users to reference ontology data directly from SQL using the semantic query operators, and make the ontology-driven applications easy to develop.
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