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Using Radial Basis Functions to Approximate the LQG-Optimal Event-Based Sampling Policy

Thelander Andrén, Marcus LU (2019) European Control Conference 2019
Abstract
A numerical method based on radial basis functions (RBF) has been developed to find the optimal event-based sampling policy in an LQG problem setting. The optimal sampling problem can be posed as a stationary partial differential equation with a free boundary, which is solved by reformulatingthe optimal RBF approximation as a linear complementarity problem (LCP). The LCP can be efficiently solved using any quadratic program solver, and we give guarantees of existence and uniqueness of the solution. The RBF method is validated numerically, and we showcase what the different types of optimal policies look like for 2D systems.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
event-based sampling, LQG-optimal control, sampled-data control, radial basis function
host publication
2019 18th European Control Conference (ECC)
publisher
Institute of Electrical and Electronics Engineers Inc.
conference name
European Control Conference 2019
conference location
Naples, Italy
conference dates
2019-06-25 - 2019-06-28
external identifiers
  • scopus:85071553505
ISBN
978-3-907144-00-8
DOI
10.23919/ECC.2019.8795838
project
Event-Based Estimation and Control
Event-Based Control of Stochastic Systems with Application to Server Systems
language
English
LU publication?
yes
id
3bf51293-a87b-45f3-a3f1-dfcaac1b423a
date added to LUP
2018-11-22 14:28:18
date last changed
2020-12-29 04:01:14
@inproceedings{3bf51293-a87b-45f3-a3f1-dfcaac1b423a,
  abstract     = {A numerical method based on radial basis functions (RBF) has been developed to find the optimal event-based sampling policy in an LQG problem setting. The optimal sampling problem can be posed as a stationary partial differential equation with a free boundary, which is solved by reformulatingthe optimal RBF approximation as a linear complementarity problem (LCP). The LCP can be efficiently solved using any quadratic program solver, and we give guarantees of existence and uniqueness of the solution. The RBF method is validated numerically, and we showcase what the different types of optimal policies look like for 2D systems.},
  author       = {Thelander Andrén, Marcus},
  booktitle    = {2019 18th European Control Conference (ECC)},
  isbn         = {978-3-907144-00-8},
  language     = {eng},
  publisher    = {Institute of Electrical and Electronics Engineers Inc.},
  title        = {Using Radial Basis Functions to Approximate the LQG-Optimal Event-Based Sampling Policy},
  url          = {https://lup.lub.lu.se/search/ws/files/69735626/paper.pdf},
  doi          = {10.23919/ECC.2019.8795838},
  year         = {2019},
}