NCS: Packet-based Control: the TCP case: Difference between revisions

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In this lecture we consider the Linear Quadratic Gaussian (LQG) optimal control problem in the discrete time setting and when data loss may occur between the sensors and the estimation-control unit and between the latter and the actuation points. We focus on the case where the arrival of the control packet is acknowledged at the receiving actuator, as it happens with the common Transfer Control Protocol (TCP). We start by showing that the separation principle holds. Additionally, we can prove that the optimal LQG control is a linear function of the state. Finally, building upon the results shown in the previous lecture on estimation with unreliable communication, we show the existence of critical arrival probabilities below which the optimal controller fails to stabilize the system. This is done by providing analytic upper and lower bounds on the cost functional.
In this lecture we consider the Linear Quadratic Gaussian (LQG) optimal control problem in the discrete time setting and when data loss may occur between the sensors and the estimation-control unit and between the latter and the actuation points. We focus on the case where the arrival of the control packet is acknowledged at the receiving actuator, as it happens with the common Transfer Control Protocol (TCP). We start by showing that the separation principle holds. Additionally, we can prove that the optimal LQG control is a linear function of the state. Finally, building upon the results shown in the previous lecture on estimation with unreliable communication, we show the existence of critical arrival probabilities below which the optimal controller fails to stabilize the system. This is done by providing analytic upper and lower bounds on the cost functional.
In the previous lectures we showed that, for protocols where
 
packets are acknowledged at the receiver (e.g.\ TCP type
protocols), the separation principle holds. Moreover, the optimal
LQG control is a linear function of the state. Finally, we showed the existence of critical arrival
probabilities below which the optimal controller fails to
stabilize the system. In this lecture we focus on UDP-like protocols. It turns out that when there is no feedback on whether a control packet has been delivered or not
(e.g. UDP type protocols), the LQG optimal controller is in
general nonlinear function of the information state. In the particular case where there is no measurement noise and the observation matrix C is invertible, we are able to show that the optimal controller is again linear, even if the separation principle still doesn't hold.
Necessary conditions on the arrival probabilities for state boundedness are provided.
== Lecture Materials ==
== Lecture Materials ==
<!-- Include links to materials that you used in your lecture.  At a minimum, this should include a link to your lecture presentation.  You might also include links to MATLAB scripts or other source code that students would find useful -->
<!-- Include links to materials that you used in your lecture.  At a minimum, this should include a link to your lecture presentation.  You might also include links to MATLAB scripts or other source code that students would find useful -->
<!-- Sample lecture link: * [[Media:L1-1_Intro.pdf|Lecture: Networked Control Systems: Course Overview]] -->
<!-- Sample lecture link: * [[Media:L1-1_Intro.pdf|Lecture: Networked Control Systems: Course Overview]] -->
* [[Media:L5-2_packet_based_control.pdf |Lecture: Packet-based Control]],
* [[Media:L5-2_packet_based_control_slides.pdf |Lecture: TCP Packet-based Control slides]]
For this lecture consider pages 71-88.
* [[Media:L5-2_packet_based_control.pdf |Lecture: TCP/UDP Packet-based Control notes]],
For this lecture consider pages 57-71.


== Reading ==
== Reading ==
* <p>[http://robotics.eecs.berkeley.edu/~sinopoli/Sinopoli_ifac.pdf LQG Control with Missing Observation and Control Packets], B. Sinopoli, L. Schenato, M. Franceschetti, K. Poolla and S. Sastry. Ifac 05</p>
* <p>[http://robotics.eecs.berkeley.edu/~sinopoli/acc05.pdf Optimal Control with Unreliable Communication: the TCP Case], B. Sinopoli, L. Schenato, M. Franceschetti, K. Poolla and S. Sastry. This is the paper where we published the results contained in the thesis</p>
 


* <p>[http://robotics.eecs.berkeley.edu/~sinopoli/cdc05.pdf    An LQG Optimal Linear Controller for Control Systems with Packet Losses], B. Sinopoli, L. Schenato, M. Franceschetti, K. Poolla and S. Sastry. CDC 05</p>


<!-- A reading list for the lecture. This will typically be 3-5 articles or book chapters that are particularly relevant to the material being presented. The reading list should be annotated to explain how the articles fit into the topic for the lecture. -->
<!-- A reading list for the lecture. This will typically be 3-5 articles or book chapters that are particularly relevant to the material being presented. The reading list should be annotated to explain how the articles fit into the topic for the lecture. -->

Latest revision as of 00:44, 7 May 2006

Prev: Packet-based Estimation Course Home Next: Packet-based control UDP

In this lecture we consider the Linear Quadratic Gaussian (LQG) optimal control problem in the discrete time setting and when data loss may occur between the sensors and the estimation-control unit and between the latter and the actuation points. We focus on the case where the arrival of the control packet is acknowledged at the receiving actuator, as it happens with the common Transfer Control Protocol (TCP). We start by showing that the separation principle holds. Additionally, we can prove that the optimal LQG control is a linear function of the state. Finally, building upon the results shown in the previous lecture on estimation with unreliable communication, we show the existence of critical arrival probabilities below which the optimal controller fails to stabilize the system. This is done by providing analytic upper and lower bounds on the cost functional.

Lecture Materials

For this lecture consider pages 57-71.

Reading



Additional Resources

Books

  • Stochastic Systems: Estimation, Identification and Adaptive Control, by P.R. Kumar, P. Varaiya, Prentice Hall, 1986. Difficult to find (Richard has a copy though). Even if it is not the most user friendly reading, chapters 6 to 8 contain a good reference for dynamic programming and LQG control.