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A Radial Basis Function Method for Approximating the Optimal Event-Based Sampling Policy

Thelander Andrén, Marcus LU (2018) ELLIIT Workshop 2018
Abstract
In networked control systems it is desirable to have efficient wireless communication (saving energy and bandwidth) while still ensuring good control performance. By abandoning periodic sampling, communication can be made more efficient by sampling and updating the control signal only "when required" based on the system’s behaviour. This is the concept of event-based control. In this work we consider the classic LQG problem with an added penalty on the average sampling rate, and derive a numerical method using radial basis functions (RBFs) to approximate the optimal sampling policy. The method is validated numerically, and we prove guaranteed uniqueness and existence of the optimal RBF weights.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to conference
publication status
published
subject
keywords
event-based control, sampled-data control, LQG-optimal control, radial basis function
conference name
ELLIIT Workshop 2018
conference location
Linköping, Sweden
conference dates
2018-10-22 - 2018-10-23
project
Event-Based Estimation and Control
Event-Based Control of Stochastic Systems with Application to Server Systems
language
English
LU publication?
yes
id
9c0b01ba-f6be-4f18-a4a3-d873b33f9e1a
date added to LUP
2018-11-22 14:53:33
date last changed
2018-11-26 06:35:35
@misc{9c0b01ba-f6be-4f18-a4a3-d873b33f9e1a,
  abstract     = {In networked control systems it is desirable to have efficient wireless communication (saving energy and bandwidth) while still ensuring good control performance. By abandoning periodic sampling, communication can be made more efficient by sampling and updating the control signal only "when required" based on the system’s behaviour. This is the concept of event-based control. In this work we consider the classic LQG problem with an added penalty on the average sampling rate, and derive a numerical method using radial basis functions (RBFs) to approximate the optimal sampling policy. The method is validated numerically, and we prove guaranteed uniqueness and existence of the optimal RBF weights.},
  author       = {Thelander Andrén, Marcus},
  language     = {eng},
  month        = {06},
  title        = {A Radial Basis Function Method for Approximating the Optimal Event-Based Sampling Policy},
  url          = {https://lup.lub.lu.se/search/ws/files/54763597/poster.pdf},
  year         = {2018},
}