An official website of the United States government
The problem of distributed networked sensor agents jointly estimating the state of a plant given by a linear time-invariant system is studied. Each agent can only measure the output of the plant at intermittent time instances, at which times the agent also sends the received plant measurement and its estimate to its neighbors. At each agent, a decentralized observer is attached which utilizes the asynchronous incoming information being sent from its neighbors to drive its own estimate to the state of the plant. We provide sufficient conditions that guarantee global exponential stability of the zero estimation error set. Numerical illustrations are provided.
more »
« less
Randomized Asynchronous Recursions with a Sinusoidal Input
This study considers a randomized asynchronous form of the discrete time-invariant state-space models, in which only a random subset of the state variables is updated in each iteration. When the system has a single input in the form of a complex exponential, it is shown that the output signal still behaves like an exponential in a statistical sense. The study presents the necessary and sufficient condition that ensures the stability of a randomized asynchronous system, which does not necessarily require the stability of the state transition matrix.
more »
« less
- Award ID(s):
- 1712633
- PAR ID:
- 10148055
- Date Published:
- Journal Name:
- Proc. Asil. Conf. Sig., Sys., and Comp.
- Page Range / eLocation ID:
- 1491 to 1495
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)Filter banks on graphs are shown to be useful for analyzing data defined over networks, as they decompose a graph signal into components with low variation and high variation. Based on recent node-asynchronous implementation of graph filters, this study proposes an asynchronous implementation of filter banks on graphs. In the proposed algorithm nodes follow a randomized collect-compute-broadcast scheme: if a node is in the passive stage it collects the data sent by its incoming neighbors and stores only the most recent data. When a node gets into the active stage at a random time instance, it does the necessary filtering computations locally, and broadcasts a state vector to its outgoing neighbors. When the underlying filters (of the filter bank) are rational functions with the same denominator, the proposed filter bank implementation does not require additional communication between the neighboring nodes. However, computations done by a node increase linearly with the number of filters in the bank. It is also proven that the proposed asynchronous implementation converges to the desired output of the filter bank in the mean-squared sense under mild stability conditions. The convergence is verified also with numerical experiments.more » « less
-
Consider a massive (inert) particle impinged from above by N Brownian particles that are instantaneously reflected upon collision with the inert particle. The velocity of the inert particle increases due to the influence of an external Newtonian potential (e.g. gravitation) and decreases in proportion to the total local time of collisions with the Brownian particles. This system models a semi-permeable membrane in a fluid having microscopic impurities (Knight in Probab Theory Relat Fields 121:577–598, 2001). We study the long-time behavior of the process (V , Z), where V is the velocity of the inert particle and Z is the vector of gaps between successive particles ordered by their relative positions. The system is not hypoelliptic, not reversible, and has singular form interactions. Thus the study of stability behavior of the system requires new ideas. We show that this process has a unique stationary distribution that takes an explicit product form which is Gaussian in the velocity component and exponential in the other components. We also show that convergence in total variation distance to the stationary distribution happens at an exponential rate. We further obtain certain law of large numbers results for the particle locations and intersection local times.more » « less
-
In this paper we study a discrete-time SIS (susceptible-infected-susceptible) model, where the infection and healing parameters and the underlying network may change over time. We provide conditions for the model to be well-defined and study its stability. For systems with homogeneous infection rates over symmetric graphs, we provide a sufficient condition for global exponential stability (GES) of the healthy state, that is, where the virus is eradicated. For systems with heterogeneous virus spread over directed graphs, provided that the variation is not too fast, a sufficient condition for GES of the healthy state is established. Appealing to the first stability result, we present two data-driven mitigation strategies that set the healing parameters in a centralized and a distributed manner, respectively, in order to drive the system to the healthy state.more » « less
-
Traditional traffic signal control focuses more on the optimization aspects whereas the stability and robustness of the closed-loop system are less studied. This paper aims to establish the stability properties of traffic signal control systems through the analysis of a practical model predictive control (MPC) scheme, which models the traffic network with the conservation of vehicles based on a store-and-forward model and attempts to balance the traffic densities. More precisely, this scheme guarantees the exponential stability of the closed-loop system under state and input constraints when the inflow is feasible and traffic demand can be fully accessed. Practical exponential stability is achieved in case of small uncertain traffic demand by a modification of the previous scheme. Simulation results of a small-scale traffic network validate the theoretical analysis.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/IEEECONF44664.2019.9048998
