# Difference between revisions of "EECI08: Packet-Based Estimation and Control"

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== Lecture Materials == | == Lecture Materials == | ||

* Lecture slides: {{eeci-sp08 pdf|L7_pbc.pdf|Packet-Based Estimation and Control}} | * Lecture notes: {{eeci-sp08 pdf|L7_pbc-notes.pdf|Packet-Based Estimation and Control}} (scan of handwritten notes) | ||

* Lecture slides: {{eeci-sp08 pdf|L7_pbc.pdf|Packet-Based Estimation and Control}} (contains a few examples + graphs) | |||

== Reading == | == Reading == |

## Revision as of 23:49, 30 March 2008

Prev: State Estimation | Course home | Next: Graph Theory |

This lecture describes how to extend results in estimation and control to the case where the information between sensing, actuation and computation flows across a network with possible packet loss and time delay. We begin with the estimation problem, summarizing the results on Sinopoli et al on Kalman filtering with intermittent data, which uses average convergence as a stability metric. An alternative formulation is to use almost sure convergence, which gives improved results for lossy networks. Finally, we extend the results on estimation to the control setting, summarizing approaches in the cases where receipt of packets are acknowledge (TCP-like) or not acknowledged (UDP-like).

## Lecture Materials

- Lecture notes: Packet-Based Estimation and Control (scan of handwritten notes)
- Lecture slides: Packet-Based Estimation and Control (contains a few examples + graphs)

## Reading

Kalman Filtering with Intermittent Observations, B. Sinopoli, L. Schenato, M. Franceschetti, K. Poolla, M. Jordan and S. Sastry.

*IEEE T. Automatic Control*, 2004. This is the paper that covers the main results of this lecture.

Probabilistic Performance of State Estimation Across a Lossy Network. Michael Epstein, Ling Shi, Abhishek Tiwari and Richard M. Murray.

*Automatica*, 2008 (to appear). This article describes how to computer probabilistic guarantees on estimator performance in the presence of packet loss.