Kalman Filtering with Intermittent Observations

Proceedings of the IEEE Conference on Decision and Control

Volumn 1, Issue , 2003, Pages 701-708

  Sinopoli, Bruno ^a   Schenato, Luca ^a   Franceschetti, Massimo ^a   Poolla, Kameshwar ^a   Jordan, Michael I ^a   Sastry, Shankar S ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHANNEL CAPACITY; CONVERGENCE OF NUMERICAL METHODS; EMBEDDED SYSTEMS; ERROR ANALYSIS; KALMAN FILTERING; LINEAR SYSTEMS; SENSORS; STATISTICAL METHODS;

COMMUNICATION DELAYS; SENSOR NETWORKS;

CONTROL SYSTEM ANALYSIS;

EID: 1542359079     PISSN: 07431546     EISSN: 25762370     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. Smart dust project home page. http://robotics.eecs.berkeley.edu/pister/SmartDust/.
2. NEST project at Berkeley home page. http://webs.cs.berkeley.edu/nest-index.html.
3. Seismic sensor research at berkeley, home page. http://www.berkeley.edu/news/media/releases/2001/12/13_snsor.html.
4. P. Varaiya, "Smart cars on smart roads: Problems of control," IEEE Transactions on Automatic Control, vol. 38(2), February 1993.
5. J. Lygeros, D. N. Godbole, and S. S. Sastry, "Verified hybrid controllers for automated vehicles," IEEE Transactions on Automatic Control, vol. 43(4), 1998.
6. B. Sinopoli, C. Sharp, S. Schaffert, L. Schenato, and S. Sastry, "Distributed control applications within sensor networks," IEEE Proceedings Special Issue on Distributed Sensor Networks, November 2003.
7. R. E. Kalman, "A new approach to linear filtering and prediction problems," Transactions of the ASME - Journal of Basic Engineering on Automatic Control, vol. 82(D), pp. 35-45, 1960.
8. P. S. Maybeck, Stochastic models, estimation, and control, ser. Mathematics in Science and Engineering, 1979, vol. 141.
9. M. Micheli and M. I. Jordan, "Random sampling of a continuous-time stochastic dynamical system," in Proceedings of 15th International Symposium on the Mathematical Theory of Networks and Systems (MTNS), University of Notre Dame, South Bend, Indiana, August 2002.
10. M. Micheli, "Random sampling of a continuous-time stochastic dynamical system: Analysis, state estimation, applications," Master's Thesis, University of California at Berkeley, Deparment of Electrical Engineering, 2001.
11. M. Athans, R. Ku, and S. B. Gershwin, "The uncertainty threshold principle, some fundamental limitations of optimal decision making under dynamic uncertainty," IEEE Transactions on Automatic Control, vol. 22(3), pp. 491-495, June 1977.
12. R. Ku and M. Athans, "Further results on the uncertainty threshold principle," IEEE Transactions on Automatic Control, vol. 22(5), pp. 491-495, October 1977.