RealTime Control Systems with Delays
(1998) In PhD Theses TFRT1049. 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:
http://lup.lub.lu.se/record/18692
 author
 Nilsson, Johan
 opponent

 Söderström, Torsten, Uppsala University
 organization
 publishing date
 1998
 type
 Thesis
 publication status
 published
 subject
 keywords
 Timing jitter, Stochastic parameters, Stochastic control, Realtime 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
 TFRT1049
 pages
 138 pages
 publisher
 Department of Automatic Control, Lund Institute of Technology (LTH)
 defense location
 M:B, Mbuilding, Lund Institute of Technology
 defense date
 19980211 10:15
 ISSN
 02805316
 language
 English
 LU publication?
 no
 id
 a7fa0a2d09ac4630bd35e9981735db27 (old id 18692)
 date added to LUP
 20070524 12:14:02
 date last changed
 20180529 10:35:54
@phdthesis{a7fa0a2d09ac4630bd35e9981735db27, 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 = {02805316}, keyword = {Timing jitter,Stochastic parameters,Stochastic control,Realtime 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 = {RealTime Control Systems with Delays}, volume = {TFRT1049}, year = {1998}, }