As modern communication networks become increasingly advanced, so does the ability and necessity to communicate to make more informed decisions. However, communication alone is not sufficient; the method by which information is incorporated and used to make the decision is of critical importance. This thesis develops a novel distributed agreement protocol that allows multiple agents to agree up...

In this paper, the problem of consensus tracking uncertain multi-agent systems (MAS) with communication faults is addressed. The assumed to be undirected. A reinforced unscented Kalman filter (RUKF) employed adapt noise covariance matrices and estimate states MAS as well train neural network internal parameters by providing a set previous measurements. Chebyshev (CNN) incorporated learn plant. ...

Without assuming that the mobile agents can communicate with their neighbors all the time, the consensus problem of multi-agent systems with general linear node dynamics and a fixed directed topology is investigated. To achieve consensus, a new class of distributed protocols designed based only on the intermittent relative information are presented. By using tools from matrix analysis and switc...

The guaranteed-performance consensus tracking (GPCT) for non-linear multi-agent systems (MASs) with switching communication topologies is presented. Different from the existing work, range of one-sided Lipschitz MASs wider than ones, and upper bound performance given while achieving tracking. First, a control protocol proposed, where regulation involved. Then, by linear matrix inequality (LMI),...

The paper addresses consensus-based networked estimation of the state of a nonlinear dynamical system. The focus is on a family of distributed state estimation algorithms which relies on the extended Kalman filter linearization paradigm. Consensus is exploited in order to fuse the information, both prior and novel, available in each network node. It is shown that the considered family of distri...

In this work, leader follower consensus objective has been addressed with the synthesis of an event based controller utilizing sliding mode robust control. The schema has been partitioned into two parts viz. finite time consensus problem and event triggered control mechanism. A nonlinear multi agent system with non identical dynamics has been put forward to illustrate the robust capabilities of...

UNLABELLED Unsupervised class discovery is a highly useful technique in cancer research, where intrinsic groups sharing biological characteristics may exist but are unknown. The consensus clustering (CC) method provides quantitative and visual stability evidence for estimating the number of unsupervised classes in a dataset. ConsensusClusterPlus implements the CC method in R and extends it with...

Object tracking is an important task for active vision and robotics. This paper presents a 3D feature-based tracker for tracking multiple moving objects with a computer-controlled binocular head. Our tracker operates in two phases: an initialization phase and a tracking phase. In the initial-ization phase, correspondence between 2D features in the first stereo image pair is determined reliably ...

Image super-resolution algorithm improves image resolution in software. Before image tracking, it needs to enhance image resolution to improve the image tracking accuracy of the bionic eye. The traditional super-resolution reconstruction method can’t satisfy the accuracy and real-time system, so this paper proposes super-resolution image reconstruction algorithm based on SURF (Speeded up Robust...