Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-20 Cooperative journals: 《计算机应用研究》
Abstract： In order to reduce the impact of communication delay on the system to achieve consensus, this paper investigates the leader-following consensus of the second-order nonlinear multi-agent systems with active leader. It presents the concept of an approximate random pulse delay, and designed a new control protocol to make the system achieve the leader-following consensus. Compared with the traditional protocol, when the pulse time communication delay is small, the agents in the new protocol predict their current state of time based on the delay state and send the prediction state to each adjacent agent, which compensate for its own feedback channel delay meanwhile. Based on the Lyapunov stability theory, using the nature of a kind of generalized Halanay inequality obtains two sufficient conditions which can guarantee the reaching of leader-following consensus of systems. Finally, the simulation of the example verifies the superiority of new protocol.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-19 Cooperative journals: 《计算机应用研究》
Abstract： To make research results more realistic , this paper studied the consensus of multi-agent systems with uncertainties and randomly occurring nonlinearities and time delay via impulsive control with topology switching. In the traditional protocol, it is usually assumed that the communication delay between adjacent individuals is the same as the communication delay between individual and leader, but this is conservative. In the new protocol, the size of delay above can be different. Compared with traditional research methods, the approach that deals with the delay in complex network synchronization research is introduced into the research of consensus of multi-agent systems. Using a generalized Halanay inequality , two sufficient conditions which are not related to the delay are given to meet the leader-following consensus of systems with topology switching, in other words, the delay does not affect the final consensus of system when the relevant parameters satisfy the theorem’s conditions. Compared with the decision conditions with delay on other methods, the results of this study are less conservative. The numerical simulation verifies the feasibility of the new protocol.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-12 Cooperative journals: 《计算机应用研究》
Abstract： Inferring causal directions from observed variables is one of the fundamental problems in artificial intelligence (AI) field. Traditional conditional independence based methods usually learn causal directions by detecting V-structures and return Markov equivalence classes, instead of true causal structures; Most other direction learning methods can distinguish the equivalence classes, but are effective only in the bivariate (or two-dimensional) cases. This paper proposed a new approach for causal direction inference from general networks, based on a split-and-merge strategy. The method first decomposes an n-dimensional network into n induced subnetworks, each of which corresponds to a node in the network. Each induced subnetwork can be subsumed to one of the three substructures: one-degree, non-triangle and triangle-existence structures. Three effective algorithms are developed to infer causalities from the three substructures, and learning these induced subnetworks orderly to achieved the whole causal structure of the multi-dimensional network. Experiments show that the method is more general and effective than traditional methods.
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