5,171 research outputs found
Exploiting timing information in event-triggered stabilization of linear systems with disturbances
In the same way that subsequent pauses in spoken language are used to convey
information, it is also possible to transmit information in communication
networks not only by message content, but also with its timing. This paper
presents an event-triggering strategy that utilizes timing information by
transmitting in a state-dependent fashion. We consider the stabilization of a
continuous-time, time-invariant, linear plant over a digital communication
channel with bounded delay and subject to bounded plant disturbances and
establish two main results. On the one hand, we design an encoding-decoding
scheme that guarantees a sufficient information transmission rate for
stabilization. On the other hand, we determine a lower bound on the information
transmission rate necessary for stabilization by any control policy
Exploiting timing information in event-triggered stabilization of linear systems with disturbances
In the same way that subsequent pauses in spoken language are used to convey information, it is also possible to transmit information in communication networks not only by message content, but also with its timing. This paper presents an event- triggering strategy that utilizes timing information by transmitting in a state-dependent fashion. We consider the stabilization of a continuous-time, time-invariant, linear plant over a digital communication channel with bounded delay and subject to bounded plant disturbances and establish two main results. On the one hand, we design an encoding-decoding scheme that guarantees a sufficient information transmission rate for stabilization. On the other hand, we determine a lower bound on the information transmission rate necessary for stabilization by any control policy
Mini-Workshop: Entropy, Information and Control
This mini-workshop was motivated by the emerging field of networked control, which combines concepts from the disciplines of control theory, information theory and dynamical systems. Many current approaches to networked control simplify one or more of these three aspects, for instance by assuming no dynamical disturbances, or noiseless communication channels, or linear dynamics. The aim of this meeting was to approach a common understanding of the relevant results and techniques from each discipline in order to study the major, multi-disciplinary problems in networked control
Neuromorphic Twins for Networked Control and Decision-Making
We consider the problem of remotely tracking the state of and unstable linear
time-invariant plant by means of data transmitted through a noisy communication
channel from an algorithmic point of view. Assuming the dynamics of the plant
are known, does there exist an algorithm that accepts a description of the
channel's characteristics as input, and returns 'Yes' if the transmission
capabilities permit the remote tracking of the plant's state, 'No' otherwise?
Does there exist an algorithm that, in case of a positive answer, computes a
suitable encoder/decoder-pair for the channel? Questions of this kind are
becoming increasingly important with regards to future communication
technologies that aim to solve control engineering tasks in a distributed
manner. In particular, they play an essential role in digital twinning, an
emerging information processing approach originally considered in the context
of Industry 4.0. Yet, the abovementioned questions have been answered in the
negative with respect to algorithms that can be implemented on idealized
digital hardware, i.e., Turing machines. In this article, we investigate the
remote state estimation problem in view of the Blum-Shub-Smale computability
framework. In the broadest sense, the latter can be interpreted as a model for
idealized analog computation. Especially in the context of neuromorphic
computing, analog hardware has experienced a revival in the past view years.
Hence, the contribution of this work may serve as a motivation for a theory of
neuromorphic twins as a counterpart to digital twins for analog hardware
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