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Identification of LTV Dynamical Models with Smooth or Discontinuous Time Evolution by means of Convex Optimization

Bagge Carlson, Fredrik LU ; Robertsson, Anders LU and Johansson, Rolf LU orcid (2018) The 14th IEEE International Conference on Control and Automation 2018
Abstract
We establish a connection between trend filtering and system identification which results in a family of new identification methods for linear, time-varying (LTV) dynamical models based on convex optimization. We demonstrate how the design of the cost function promotes a model with either a continuous change in dynamics over time, or causes discontinuous changes in model coefficients occurring at a finite (sparse) set of time instances. We further discuss the introduction of priors on the model parameters for situations where excitation is insufficient for identification. The identification problems are cast as convex optimization problems and are applicable to, e.g., ARX models and state-space models with time-varying parameters. We... (More)
We establish a connection between trend filtering and system identification which results in a family of new identification methods for linear, time-varying (LTV) dynamical models based on convex optimization. We demonstrate how the design of the cost function promotes a model with either a continuous change in dynamics over time, or causes discontinuous changes in model coefficients occurring at a finite (sparse) set of time instances. We further discuss the introduction of priors on the model parameters for situations where excitation is insufficient for identification. The identification problems are cast as convex optimization problems and are applicable to, e.g., ARX models and state-space models with time-varying parameters. We illustrate usage of the methods in simulations of jump-linear systems, a nonlinear robot arm with non-smooth friction and stiff contacts as well as in model-based, trajectory centric reinforcement learning on a smooth nonlinear system. (Less)
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2018 IEEE 14th International Conference on Control and Automation (ICCA)
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
The 14th IEEE International Conference on Control and Automation 2018
conference location
Anchorage, Alaska, United States
conference dates
2018-06-12 - 2018-06-15
external identifiers
  • scopus:85053136742
ISBN
978-1-5386-6089-8
DOI
10.1109/ICCA.2018.8444351
project
LU Robotics Laboratory
SARAFun—Smart Assembly Robot with Advanced FUNctionalities
language
English
LU publication?
yes
id
77744001-8e67-4db9-b0ac-e493fec7e957
date added to LUP
2018-02-27 11:51:51
date last changed
2021-08-18 03:16:45
@inproceedings{77744001-8e67-4db9-b0ac-e493fec7e957,
  abstract     = {We establish a connection between trend filtering and system identification which results in a family of new identification methods for linear, time-varying (LTV) dynamical models based on convex optimization. We demonstrate how the design of the cost function promotes a model with either a continuous change in dynamics over time, or causes discontinuous changes in model coefficients occurring at a finite (sparse) set of time instances. We further discuss the introduction of priors on the model parameters for situations where excitation is insufficient for identification. The identification problems are cast as convex optimization problems and are applicable to, e.g., ARX models and state-space models with time-varying parameters. We illustrate usage of the methods in simulations of jump-linear systems, a nonlinear robot arm with non-smooth friction and stiff contacts as well as in model-based, trajectory centric reinforcement learning on a smooth nonlinear system.},
  author       = {Bagge Carlson, Fredrik and Robertsson, Anders and Johansson, Rolf},
  booktitle    = {2018 IEEE 14th International Conference on Control and Automation (ICCA)},
  isbn         = {978-1-5386-6089-8},
  language     = {eng},
  month        = {02},
  publisher    = {IEEE - Institute of Electrical and Electronics Engineers Inc.},
  title        = {Identification of LTV Dynamical Models with Smooth or Discontinuous Time Evolution by means of Convex Optimization},
  url          = {https://lup.lub.lu.se/search/files/39151925/id_paper.pdf},
  doi          = {10.1109/ICCA.2018.8444351},
  year         = {2018},
}