23,497 research outputs found
Event-triggered distributed H∞ state estimation with packet dropouts through sensor networks
This study is concerned with the event-triggered distributed H∞ state estimation problem for a class of discrete-time stochastic non-linear systems with packet dropouts in a sensor network. An event-triggered communication mechanism is adopted over the sensor network with hope to reduce the communication burden and the energy consumption, where the measurements on each sensor are transmitted only when a certain triggering condition is violated. Furthermore, a novel distributed state estimator is designed where the available innovations are not only from the individual sensor, but also from its neighbouring ones according to the given topology. The purpose of the problem under consideration is to design a set of distributed state estimators such that the dynamics of estimation errors is exponentially mean-square stable and also the prespecified H∞ disturbance rejection attenuation level is guaranteed. By utilising the property of the Kronecker product and the stochastic analysis approaches, sufficient conditions are established under which the addressed state estimation problem is recast as a convex optimisation one that can be easily solved via available software packages. Finally, a simulation example is utilised to illustrate the usefulness of the proposed design scheme of event-triggered distributed state estimators.This work was supported in part by Royal Society of the UK, the National Natural Science Foundation of China under Grants 61329301, 61203139, 61473076, 61374127 and 61422301, the Shanghai Rising-Star Program of China under Grant 13QA1400100, the ShuGuang project of Shanghai Municipal Education Commission and Shanghai Education Development Foundation under Grant 13SG34, the Fundamental Research Funds for the Central Universities, DHU Distinguished Young Professor Program, and the Alexander von Humboldt Foundation of Germany
Distributed convex optimization via continuous-time coordination algorithms with discrete-time communication
This paper proposes a novel class of distributed continuous-time coordination
algorithms to solve network optimization problems whose cost function is a sum
of local cost functions associated to the individual agents. We establish the
exponential convergence of the proposed algorithm under (i) strongly connected
and weight-balanced digraph topologies when the local costs are strongly convex
with globally Lipschitz gradients, and (ii) connected graph topologies when the
local costs are strongly convex with locally Lipschitz gradients. When the
local cost functions are convex and the global cost function is strictly
convex, we establish asymptotic convergence under connected graph topologies.
We also characterize the algorithm's correctness under time-varying interaction
topologies and study its privacy preservation properties. Motivated by
practical considerations, we analyze the algorithm implementation with
discrete-time communication. We provide an upper bound on the stepsize that
guarantees exponential convergence over connected graphs for implementations
with periodic communication. Building on this result, we design a
provably-correct centralized event-triggered communication scheme that is free
of Zeno behavior. Finally, we develop a distributed, asynchronous
event-triggered communication scheme that is also free of Zeno with asymptotic
convergence guarantees. Several simulations illustrate our results.Comment: 12 page
Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems
There is a trend towards using wireless technologies in networked control
systems. However, the adverse properties of the radio channels make it
difficult to design and implement control systems in wireless environments. To
attack the uncertainty in available communication resources in wireless control
systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS)
scheme is developed, which takes advantage of the co-design of control and
wireless communications. By exploiting cross-layer design, CLAFS adjusts the
sampling periods of control systems at the application layer based on
information about deadline miss ratio and transmission rate from the physical
layer. Within the framework of feedback scheduling, the control performance is
maximized through controlling the deadline miss ratio. Key design parameters of
the feedback scheduler are adapted to dynamic changes in the channel condition.
An event-driven invocation mechanism for the feedback scheduler is also
developed. Simulation results show that the proposed approach is efficient in
dealing with channel capacity variations and noise interference, thus providing
an enabling technology for control over WLAN.Comment: 17 pages, 12 figures; Open Access at
http://www.mdpi.org/sensors/papers/s8074265.pd
- …