The distributed estimation problem is solved for continuous-time observer nodes that obtain real-time measurements but communicate with their neighbors over a communication network. To this end, the digital communicat...
详细信息
The distributed estimation problem is solved for continuous-time observer nodes that obtain real-time measurements but communicate with their neighbors over a communication network. To this end, the digital communication between the observer nodes is modeled by the time-delay approach where variable sampling intervals, transmission delays, and packet dropouts are taken into account. An LMI for the design of the observer gains is derived using Halanay's inequality, the feasibility of which guarantees exponential stability with a selected convergence rate up to a maximum total delay. A comparison of the maximal delay on a numerical example shows the advantage of a distributed observer over a centralized one.
In this study, the authors consider distributedestimation over a sensor network with limited power. Based on PageRank algorithm, they propose a distributed estimator, where the link weight is designed using online in...
详细信息
In this study, the authors consider distributedestimation over a sensor network with limited power. Based on PageRank algorithm, they propose a distributed estimator, where the link weight is designed using online information. They compared the network performance of the proposed estimator with time-varying weight and constant weight under identical initial conditions. To extend the lifetime of sensors, they introduce an online power scheduling method to distributed estimation problem, where each sensor allocates the power for the communication link based on real-time estimation error. They also provide a sufficient condition to guarantee the stability of the networked system with power scheduling.
To deal with the distributed estimation problem for mobile sensor networks with non-linear systems and a large amount of data transfer, the distributed event-triggered cubature information filtering based on weighted ...
详细信息
To deal with the distributed estimation problem for mobile sensor networks with non-linear systems and a large amount of data transfer, the distributed event-triggered cubature information filtering based on weighted average consensus is proposed. The filter benefits from the non-linear filtering algorithm with consensus technique and event-triggered mechanism which reduces the amount of data transfer. The triggering decision is based on the data transmission mechanism, which is that each sensor makes a request to exchange information with its neighbours only if the difference between the most recent transmitted estimate and the current estimate exceeds a tolerable threshold. The estimation error of the proposed filter is proved to be bounded in mean square. Finally, numerical examples are provided to demonstrate the effectiveness of the theoretical results.
The distributed estimation problem for wireless sensor networks with limited communication/sensing ranges and observability is studied. A novel sensor measuring activation scheme based on a fully distributed event-tri...
详细信息
The distributed estimation problem for wireless sensor networks with limited communication/sensing ranges and observability is studied. A novel sensor measuring activation scheme based on a fully distributed event-triggered strategy is proposed to make each node achieve a better trade-off between estimation error and energy saving. The strategy depends on both the predicted synthetic performance index and the predicted position of the target. A distributed Kalman filtering algorithm based on the minimum trace fusion principle is proposed. It is proved that comparing with the time-triggered strategy, the proposed event-triggered measuring strategy has better performance. Although the event-triggered measuring topology is time-varying and each sensor is not observable, it is proved that as long as there exists at least one collaboratively observable sensor in the available distance-based sensing network at each time instant, the estimation errors are bounded in mean square sense. Simulation examples are given to illustrate the validity of the algorithm.
The robust distributedestimation for a class of time-invariant plants is achieved via a finite-time observer, its error reaching zero after a finite time in the absence of perturbation. Two types of robustness are al...
详细信息
The robust distributedestimation for a class of time-invariant plants is achieved via a finite-time observer, its error reaching zero after a finite time in the absence of perturbation. Two types of robustness are also shown. First, input-to-state stability with respect to measurement noises and additive perturbations is proven. Second, we demonstrate that the estimation error stays bounded in the presence of known transmission delays.
暂无评论