EECI08: State Estimation on Lattices: Difference between revisions

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This lecture describes how to perform estimation and control in a distributed setting.
We address the problem of estimating discrete variables in a class of deterministic transition systems in which the continuous variables are available for measurement. We propose a novel approach to the estimation of discrete variables using lattice theory that overcomes some of the severe complexity issues encountered in previous work. The methodology proposed for the estimation of discrete variables is general as it is applicable to any observable system. Extensions generalize the approach to nondeterministic transition systems. The proposed estimator is finally constructed for a multi-robot system involving two teams competing against each other.


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== Lecture Materials ==
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* Lecture slides: {{eeci-sp08 pdf|L12_lattice.pdf|Observability of Guarded Command Programs}}
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==== Outline ====
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====  Lecture Materials ====
== Further Reading ==
* Lecture slides: {{eeci-sp08 pdf placeholder|L7_pbc.pdf|Distributed Estimation and Control}}
* D. Del Vecchio, R. M. Murray, and E. Klavins, “Discrete State Estimators for Systems on a Lattice”, Automatica, vol. 42, pp. 271-285, 2006.
* Lecture notes: {{ncsbook|fusion|Chapter 6 - Distributed Estimation and Control}}
 
====  Additional Information ====
 
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==== Further Reading ====

Latest revision as of 20:17, 1 March 2009

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We address the problem of estimating discrete variables in a class of deterministic transition systems in which the continuous variables are available for measurement. We propose a novel approach to the estimation of discrete variables using lattice theory that overcomes some of the severe complexity issues encountered in previous work. The methodology proposed for the estimation of discrete variables is general as it is applicable to any observable system. Extensions generalize the approach to nondeterministic transition systems. The proposed estimator is finally constructed for a multi-robot system involving two teams competing against each other.

Lecture Materials

Further Reading

  • D. Del Vecchio, R. M. Murray, and E. Klavins, “Discrete State Estimators for Systems on a Lattice”, Automatica, vol. 42, pp. 271-285, 2006.