Using Radial Basis Functions to Approximate the LQG-Optimal Event-Based Sampling Policy
(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:
https://lup.lub.lu.se/record/3bf51293-a87b-45f3-a3f1-dfcaac1b423a
- author
- Thelander Andrén, Marcus LU
- organization
- publishing date
- 2019
- 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
- IEEE - 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
- 2024-01-01 19:28:57
@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}}, keywords = {{event-based sampling; LQG-optimal control; sampled-data control; radial basis function}}, language = {{eng}}, publisher = {{IEEE - 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/files/69735626/paper.pdf}}, doi = {{10.23919/ECC.2019.8795838}}, year = {{2019}}, }