206 research outputs found
Distributed estimation over a low-cost sensor network: a review of state-of-the-art
Proliferation of low-cost, lightweight, and power efficient sensors and advances in networked systems enable the employment of multiple sensors. Distributed estimation provides a scalable and fault-robust fusion framework with a peer-to-peer communication architecture. For this reason, there seems to be a real need for a critical review of existing and, more importantly, recent advances in the domain of distributed estimation over a low-cost sensor network. This paper presents a comprehensive review of the state-of-the-art solutions in this research area, exploring their characteristics, advantages, and challenging issues. Additionally, several open problems and future avenues of research are highlighted
Performance analysis with network-enhanced complexities: On fading measurements, event-triggered mechanisms, and cyber attacks
Copyright © 2014 Derui Ding et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Nowadays, the real-world systems are usually subject to various complexities such as parameter uncertainties, time-delays, and nonlinear disturbances. For networked systems, especially large-scale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities because of the usage of the communication networks. Therefore, it would be interesting to (1) examine how this kind of network-enhanced complexities affects the control or filtering performance; and (2) develop some suitable approaches for controller/filter design problems. In this paper, we aim to survey some recent advances on the performance analysis and synthesis with three sorts of fashionable network-enhanced complexities, namely, fading measurements, event-triggered mechanisms, and attack behaviors of adversaries. First, these three kinds of complexities are introduced in detail according to their engineering backgrounds, dynamical characteristic, and modelling techniques. Then, the developments of the performance analysis and synthesis issues for various networked systems are systematically reviewed. Furthermore, some challenges are illustrated by using a thorough literature review and some possible future research directions are highlighted.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 61203139, 61374127, and 61374010, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
Improved Distributed Estimation Method for Environmental\ud time-variant Physical variables in Static Sensor Networks
In this paper, an improved distributed estimation scheme for static sensor networks is developed. The scheme is developed for environmental time-variant physical variables. The main contribution of this work is that the algorithm in [1]-[3] has been extended, and a filter has been designed with weights, such that the variance of the estimation errors is minimized, thereby improving the filter design considerably\ud
and characterizing the performance limit of the filter, and thereby tracking a time-varying signal. Moreover, certain parameter optimization is alleviated with the application of a particular finite impulse response (FIR) filter. Simulation results are showing the effectiveness of the developed estimation algorithm
Event-Triggered Consensus and Formation Control in Multi-Agent Coordination
The focus of this thesis is to study distributed event-triggered
control for multi-agent systems (MASs) facing constraints in
practical applications. We consider several problems in the
field, ranging from event-triggered consensus with information
quantization, event-triggered edge agreement under
synchronized/unsynchronized clocks, event-triggered
leader-follower consensus with Euler-Lagrange agent dynamics and
cooperative event-triggered rigid formation control.
The first topic is named as event-triggered consensus with
quantized relative state measurements. In this topic, we develop
two event-triggered controllers with quantized relative state
measurements to achieve consensus for an undirected network where
each agent is modelled by single integrator dynamics. Both
uniform and logarithmic quantizers are considered, which,
together with two different controllers, yield four cases of
study in this topic. The quantized information is used to update
the control input as well as to determine the next trigger event.
We show that approximate consensus can be achieved by the
proposed algorithms and Zeno behaviour can be completely excluded
if constant offsets with some computable lower bounds are added
to the trigger conditions.
The second topic considers event-triggered edge agreement
problems. Two cases, namely the synchronized clock case and the
unsynchronized clock case, are studied. In the synchronized clock
case, all agents are activated simultaneously to measure the
relative state information over edge links under a global clock.
Edge events are defined and their occurrences trigger the update
of control inputs for the two agents sharing the link. We show
that average consensus can be achieved with our proposed
algorithm. In the unsynchronized clock case, each agent executes
control algorithms under its own clock which is not synchronized
with other agents' clocks. An edge event only triggers control
input update for an individual agent. It is shown that all agents
will reach consensus in a totally asynchronous manner.
In the third topic, we propose three different distributed
event-triggered control algorithms to achieve leader-follower
consensus for a network of Euler-Lagrange agents. We firstly
propose two model-independent algorithms for a subclass of
Euler-Lagrange agents without the vector of gravitational
potential forces. A variable-gain algorithm is employed when the
sensing graph is undirected; algorithm parameters are selected in
a fully distributed manner with much greater flexibility compared
to all previous work concerning event-triggered consensus
problems. When the sensing graph is directed, a constant-gain
algorithm is employed. The control gains must be centrally
designed to exceed several lower bounding inequalities which
require limited knowledge of bounds on the matrices describing
the agent dynamics, bounds on network topology information and
bounds on the initial conditions. When the Euler-Lagrange agents
have dynamics which include the vector of gravitational potential
forces, an adaptive algorithm is proposed. This requires more
information about the agent dynamics but allows for the
estimation of uncertain agent parameters.
The last topic discusses cooperative stabilization control of
rigid formations via an event-triggered approach. We first design
a centralized event-triggered formation control system, in which
a central event controller determines the next triggering time
and broadcasts the event signal to all the agents for control
input update. We then build on this approach to propose a
distributed event control strategy, in which each agent can use
its local event trigger and local information to update the
control input at its own event time. For both cases, the trigger
condition, event function and trigger behaviour are discussed in
detail, and the exponential convergence of the formation system
is guaranteed
Non-fragile estimation for discrete-time T-S fuzzy systems with event-triggered protocol
summary:This paper investigates the non-fragile state estimation problem for a class of discrete-time T-S fuzzy systems with time-delays and multiple missing measurements under event-triggered mechanism. First of all, the plant is subject to the time-varying delays and the stochastic disturbances. Next, a random white sequence, the element of which obeys a general probabilistic distribution defined on , is utilized to formulate the occurrence of the missing measurements. Also, an event generator function is employed to regulate the transmission of data to save the precious energy. Then, a non-fragile state estimator is constructed to reflect the randomly occurring gain variations in the implementing process. By means of the Lyapunov-Krasovskii functional, the desired sufficient conditions are obtained such that the Takagi-Sugeno (T-S) fuzzy estimation error system is exponentially ultimately bounded in the mean square. And then the upper bound is minimized via the robust optimization technique and the estimator gain matrices can be calculated. Finally, a simulation example is utilized to demonstrate the effectiveness of the state estimation scheme proposed in this paper
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Communication-protocol-based analysis and synthesis of networked systems: progress, prospects and challenges
In recent years, the communication-protocol-based synthesis and analysis issues have gained substantial research interest owing mainly to their significance in networked systems. In this work, we survey the control and filtering problems of networked systems under the effects induced by communication protocols. First, we introduce the engineering background of networked systems as well as the theoretical frameworks established to deal with the communication-protocol-based analysis and synthesis problems. Then, recent advances (especially the latest results) are reviewed on the stability analysis issue subject to protocol scheduling. Subsequently, the particular effort is devoted to presenting the latest progress on various communication-protocol-based control and filtering problems according to the characteristics of networked systems (e.g. time-varying nature, random behaviours, types of parameter uncertainties, and kinds of distributed structure). After that, we provide a systematic review of the communication-protocol-based fault diagnosis problems. Finally, some research challenges of communication-protocol-based control and filtering problems are outlined for future research
Scalable and adaptable tracking of humans in multiple camera systems
The aim of this thesis is to track objects on a network of cameras both within [intra) and across (inter) cameras. The algorithms must be adaptable to change and are learnt in a scalable approach. Uncalibrated cameras are used that are patially separated, and therefore tracking must be able to cope with object oclusions, illuminations changes, and gaps between cameras.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Communication Efficiency in Information Gathering through Dynamic Information Flow
This thesis addresses the problem of how to improve the performance of multi-robot information gathering tasks by actively controlling the rate of communication between robots. Examples of such tasks include cooperative tracking and cooperative environmental monitoring. Communication is essential in such systems for both decentralised data fusion and decision making, but wireless networks impose capacity constraints that are frequently overlooked. While existing research has focussed on improving available communication throughput, the aim in this thesis is to develop algorithms that make more efficient use of the available communication capacity. Since information may be shared at various levels of abstraction, another challenge is the decision of where information should be processed based on limits of the computational resources available. Therefore, the flow of information needs to be controlled based on the trade-off between communication limits, computation limits and information value. In this thesis, we approach the trade-off by introducing the dynamic information flow (DIF) problem. We suggest variants of DIF that either consider data fusion communication independently or both data fusion and decision making communication simultaneously. For the data fusion case, we propose efficient decentralised solutions that dynamically adjust the flow of information. For the decision making case, we present an algorithm for communication efficiency based on local LQ approximations of information gathering problems. The algorithm is then integrated with our solution for the data fusion case to produce a complete communication efficiency solution for information gathering. We analyse our suggested algorithms and present important performance guarantees. The algorithms are validated in a custom-designed decentralised simulation framework and through field-robotic experimental demonstrations
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