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Timing analysis and simulation tools for real-time control

Årzén, Karl-Erik LU (2005) In Formal Modeling and Analysis of Timed Systems (Lecture Notes in Computer Science) 3829. p.142-143
Abstract (Swedish)
Abstract in Undetermined

The temporal non-determinism introduced by computing and communication in the form of delay and jitter can lead to significant performance degradation. To achieve good performance in systems with limited computer resources, e.g. embedded systems, the resource constraints of the implementation platform must be taken into account at design time. To facilitate this, software tools are needed to analyze and simulate how the timing affects the control performance. Recently two new such tools, JITTERBUG and TRUETIME have been developed at the Department of Automatic Control, Lund University.JITTERBUG is a MATLAB-based toolbox that makes it possible to compute a quadratic performance criterion for a linear... (More)
Abstract in Undetermined

The temporal non-determinism introduced by computing and communication in the form of delay and jitter can lead to significant performance degradation. To achieve good performance in systems with limited computer resources, e.g. embedded systems, the resource constraints of the implementation platform must be taken into account at design time. To facilitate this, software tools are needed to analyze and simulate how the timing affects the control performance. Recently two new such tools, JITTERBUG and TRUETIME have been developed at the Department of Automatic Control, Lund University.JITTERBUG is a MATLAB-based toolbox that makes it possible to compute a quadratic performance criterion for a linear control system under various timing conditions. The tool can also compute the spectral density of the signals in the system. Using the toolbox, one can easily and quickly assert how sensitive a control system is to delay, jitter, lost samples, etc., without resorting to simulation. The tool is quite general and can also be used to investigate jitter-compensating controllers, aperiodic controllers, and multi-rate controllers. The main contribution of the toolbox, which is built on well-known theory (LQG theory and jump linear systems), is to make it easy to apply this type of stochastic analysis to a wide range of problems.The use of JITTERBUG assumes knowledge of sampling period and latency distributions. This information can be difficult to obtain without access to measurements from the true target system under implementation. Also, the analysis cannot capture all the details and nonlinearities (especially in the real-time scheduling) of the computer system. A natural approach is to use simulation instead. However, today’s simulation tools make it difficult to simulate the true temporal behaviour of control loops. What is normally done is to introduce time delays in the control loop representing average-case or worst-case delays. Taking a different approach, the MATLAB/Simulink-based tool TRUETIME facilitates simulation of the temporal behaviour of a multitasking real-time kernel executing controller tasks. The tasks are controlling processes that are modelled as ordinary Simulink blocks. TRUETIME also makes it possible to simulate simple models of wired and wireless communication networks and their influence on networked control loops. Different scheduling policies may be used (e.g., priority-based preemptive scheduling and earliest-deadline-first (EDF) scheduling).TRUETIME can also be used as an experimental platform for research on dynamic real-time control systems. For instance, it is possible to study compensation schemes that adjust the control algorithm based on measurements of actual timing variations (i.e., to treat the temporal uncertainty as a disturbance and manage it with feed-forward or gain-scheduling). It is also easy to experiment with more flexible approaches to real-time scheduling of controllers, such as feedback scheduling [1]. There the available CPU or network resources are dynamically distributed according the current situation (CPU load, the performance of the different loops, etc.) in the system.More information about JITTERBUG and TRUETIME can be found in [2]. The toolboxes can be downloaded from http://www.control.lth.se/user/dan/truetime/ and http://www.control.lth.se/user/lincoln/jitterbug/ (Less)
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
embedded systems, networked control loops, real-time control, Co-design, simulation
in
Formal Modeling and Analysis of Timed Systems (Lecture Notes in Computer Science)
editor
Pettersson, Paul; Yi, Wang; and
volume
3829
pages
142 - 143
publisher
Springer
external identifiers
  • wos:000234886600012
  • scopus:33745442805
ISSN
1611-3349
0302-9743
ISBN
978-3-540-30946-8
DOI
10.1007/11603009_12
language
English
LU publication?
yes
id
39a721cb-1dbb-4dc8-ad07-c8797da88530 (old id 209469)
date added to LUP
2007-09-13 18:08:56
date last changed
2017-04-16 03:35:41
@inbook{39a721cb-1dbb-4dc8-ad07-c8797da88530,
  abstract     = {<b>Abstract in Undetermined</b><br/><br>
The temporal non-determinism introduced by computing and communication in the form of delay and jitter can lead to significant performance degradation. To achieve good performance in systems with limited computer resources, e.g. embedded systems, the resource constraints of the implementation platform must be taken into account at design time. To facilitate this, software tools are needed to analyze and simulate how the timing affects the control performance. Recently two new such tools, JITTERBUG and TRUETIME have been developed at the Department of Automatic Control, Lund University.JITTERBUG is a MATLAB-based toolbox that makes it possible to compute a quadratic performance criterion for a linear control system under various timing conditions. The tool can also compute the spectral density of the signals in the system. Using the toolbox, one can easily and quickly assert how sensitive a control system is to delay, jitter, lost samples, etc., without resorting to simulation. The tool is quite general and can also be used to investigate jitter-compensating controllers, aperiodic controllers, and multi-rate controllers. The main contribution of the toolbox, which is built on well-known theory (LQG theory and jump linear systems), is to make it easy to apply this type of stochastic analysis to a wide range of problems.The use of JITTERBUG assumes knowledge of sampling period and latency distributions. This information can be difficult to obtain without access to measurements from the true target system under implementation. Also, the analysis cannot capture all the details and nonlinearities (especially in the real-time scheduling) of the computer system. A natural approach is to use simulation instead. However, today’s simulation tools make it difficult to simulate the true temporal behaviour of control loops. What is normally done is to introduce time delays in the control loop representing average-case or worst-case delays. Taking a different approach, the MATLAB/Simulink-based tool TRUETIME facilitates simulation of the temporal behaviour of a multitasking real-time kernel executing controller tasks. The tasks are controlling processes that are modelled as ordinary Simulink blocks. TRUETIME also makes it possible to simulate simple models of wired and wireless communication networks and their influence on networked control loops. Different scheduling policies may be used (e.g., priority-based preemptive scheduling and earliest-deadline-first (EDF) scheduling).TRUETIME can also be used as an experimental platform for research on dynamic real-time control systems. For instance, it is possible to study compensation schemes that adjust the control algorithm based on measurements of actual timing variations (i.e., to treat the temporal uncertainty as a disturbance and manage it with feed-forward or gain-scheduling). It is also easy to experiment with more flexible approaches to real-time scheduling of controllers, such as feedback scheduling [1]. There the available CPU or network resources are dynamically distributed according the current situation (CPU load, the performance of the different loops, etc.) in the system.More information about JITTERBUG and TRUETIME can be found in [2]. The toolboxes can be downloaded from http://www.control.lth.se/user/dan/truetime/ and http://www.control.lth.se/user/lincoln/jitterbug/},
  author       = {Årzén, Karl-Erik},
  editor       = {Pettersson, Paul and Yi, Wang},
  isbn         = {978-3-540-30946-8},
  issn         = {1611-3349},
  keyword      = {embedded systems,networked control loops,real-time control,Co-design,simulation},
  language     = {eng},
  pages        = {142--143},
  publisher    = {Springer},
  series       = {Formal Modeling and Analysis of Timed Systems (Lecture Notes in Computer Science)},
  title        = {Timing analysis and simulation tools for real-time control},
  url          = {http://dx.doi.org/10.1007/11603009_12},
  volume       = {3829},
  year         = {2005},
}