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Real-Time Control Systems with Delays

Nilsson, Johan (1998) In PhD Theses TFRT-1049.
Abstract
Control loops that are closed over a communication network get more and more common. A problem with such systems is that the transfer delays will be varying with different characteristics depending on the network hardware and software. The network delays are typically varying due to varying network load, scheduling policies in the network and the nodes, and due to network failures. Two network models of different complexity are studied:



Random delays that are independent from transfer to transfer,



Random delays with probability distribution functions governed by an underlying Markov chain.



The delay models are verified by experimental measurements of network delays.

... (More)
Control loops that are closed over a communication network get more and more common. A problem with such systems is that the transfer delays will be varying with different characteristics depending on the network hardware and software. The network delays are typically varying due to varying network load, scheduling policies in the network and the nodes, and due to network failures. Two network models of different complexity are studied:



Random delays that are independent from transfer to transfer,



Random delays with probability distribution functions governed by an underlying Markov chain.



The delay models are verified by experimental measurements of network delays.



In the thesis it is shown how to analyze stability and expected performance of linear controllers where the network delays are described by one of the two network models above. Methods to evaluate quadratic cost functions are developed. Through the same analysis we find criteria for mean square stability of the closed loop for the different network models.



The Linear Quadratic Gaussian (LQG) optimal controller is developed for the two delay models. The derived controller uses knowledge of old time delays. These can be calculated using ``timestamping'' of messages in the network. ``Timestamping'' means that every transfered signal is marked with the time of generation. The receiving node can then calculate how long the transfer delay was by comparing the timestamp with the node's internal clock. (Less)
Please use this url to cite or link to this publication:
author
opponent
  • Söderström, Torsten, Uppsala University
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Timing jitter, Stochastic parameters, Stochastic control, Real-time systems, Linear quadratic control, Jump linear systems, Distributed computer control systems, Clock synchronization, Delay compensation, Automation, robotics, control engineering, Automatiska system, robotteknik, reglerteknik
in
PhD Theses
volume
TFRT-1049
pages
138 pages
publisher
Department of Automatic Control, Lund Institute of Technology (LTH)
defense location
M:B, M-building, Lund Institute of Technology
defense date
1998-02-11 10:15
ISSN
0280-5316
language
English
LU publication?
no
id
a7fa0a2d-09ac-4630-bd35-e9981735db27 (old id 18692)
date added to LUP
2007-05-24 12:14:02
date last changed
2016-10-21 12:13:03
@phdthesis{a7fa0a2d-09ac-4630-bd35-e9981735db27,
  abstract     = {Control loops that are closed over a communication network get more and more common. A problem with such systems is that the transfer delays will be varying with different characteristics depending on the network hardware and software. The network delays are typically varying due to varying network load, scheduling policies in the network and the nodes, and due to network failures. Two network models of different complexity are studied:<br/><br>
<br/><br>
Random delays that are independent from transfer to transfer,<br/><br>
<br/><br>
Random delays with probability distribution functions governed by an underlying Markov chain.<br/><br>
<br/><br>
The delay models are verified by experimental measurements of network delays.<br/><br>
<br/><br>
In the thesis it is shown how to analyze stability and expected performance of linear controllers where the network delays are described by one of the two network models above. Methods to evaluate quadratic cost functions are developed. Through the same analysis we find criteria for mean square stability of the closed loop for the different network models.<br/><br>
<br/><br>
The Linear Quadratic Gaussian (LQG) optimal controller is developed for the two delay models. The derived controller uses knowledge of old time delays. These can be calculated using ``timestamping'' of messages in the network. ``Timestamping'' means that every transfered signal is marked with the time of generation. The receiving node can then calculate how long the transfer delay was by comparing the timestamp with the node's internal clock.},
  author       = {Nilsson, Johan},
  issn         = {0280-5316},
  keyword      = {Timing jitter,Stochastic parameters,Stochastic control,Real-time systems,Linear quadratic control,Jump linear systems,Distributed computer control systems,Clock synchronization,Delay compensation,Automation,robotics,control engineering,Automatiska system,robotteknik,reglerteknik},
  language     = {eng},
  pages        = {138},
  publisher    = {Department of Automatic Control, Lund Institute of Technology (LTH)},
  series       = {PhD Theses},
  title        = {Real-Time Control Systems with Delays},
  volume       = {TFRT-1049},
  year         = {1998},
}