Vai ai contenuti. | Spostati sulla navigazione | Spostati sulla ricerca | Vai al menu | Contatti | Accessibilità

| Crea un account

Carli, Ruggero - Chiuso, Alessandro - Schenato, Luca - Zampieri, Sandro (2007) Distributed Kalman filtering based on consensus strategies. [Rapporto tecnico/Working paper] (In pubblicazione)

Full text disponibile come:

[img]
Anteprima
Documento PDF
361Kb

Abstract (inglese)

In this paper, we consider the problem of estimating the state of a dynamical system from distributed
noisy measurements. Each agent constructs a local estimate based on its own measurements and estimates
from its neighbors. Estimation is performed via a two stage strategy, the first being a Kalman-like
measurement update which does not require communication, and the second being an estimate fusion
using a consensus matrix. In particular we study the interaction between the consensus matrix, the
number of messages exchanged per sampling time, and the Kalman gain. We prove that optimizing
the consensus matrix for fastest convergence and using the centralized optimal gain is not necessarily
the optimal strategy if the number of exchanged messages per sampling time is small. Moreover, we
showed that although the joint optimization of the consensus matrix and the Kalman gain is in general
a non-convex problem, it is possible to compute them under some important scenarios. We also provide
some numerical examples to clarify some of the analytical results and compare them with alternative
estimation strategies.


Statistiche Download - Aggiungi a RefWorks
Tipo di EPrint:Rapporto tecnico/Working paper
Anno di Pubblicazione:21 Maggio 2007
Parole chiave (italiano / inglese):Consensus algorithms, Kalman Filtering, Distributed estimation
Settori scientifico-disciplinari MIUR:Area 09 - Ingegneria industriale e dell'informazione > ING-INF/04 Automatica
Struttura di riferimento:Dipartimenti > Dipartimento di Ingegneria dell'Informazione
Codice ID:90
Depositato il:20 Mag 2007
Simple Metadata
Full Metadata
EndNote Format

Bibliografia

I riferimenti della bibliografia possono essere cercati con Cerca la citazione di AIRE, copiando il titolo dell'articolo (o del libro) e la rivista (se presente) nei campi appositi di "Cerca la Citazione di AIRE".
Le url contenute in alcuni riferimenti sono raggiungibili cliccando sul link alla fine della citazione (Vai!) e tramite Google (Ricerca con Google). Il risultato dipende dalla formattazione della citazione.

P. Alriksson and A. Rantzer. Distributed Kalman filtering using weighted averaging. In Proceedings of the 17th International Symposium on Mathematical Theory of Networks and Systems, Kyoto, Japan, 2006. Cerca con Google

L. Babai. Spectra of Cayley graphs. Journal of Combinatorial Theory, Series B, 27:180—189, 1979. Cerca con Google

P. Barooah and J.P.Hespanha. Distributed estimation from relative measurements in sensor networks. In Proc. of the 2nd Int. Conf. on Intelligent Sensing and Information Processing, Dec. 2005. Cerca con Google

E. Behrends. Introduction to Markov Chains (with Special Emphasis on Rapid Mixing). Vieweg Verlag, 1999. Cerca con Google

J.-M. Borwein and A.-S. Lewis. Convex Analysis and Nonlinear Optimazation. CMS Books in Mathematics. Canadian Mathematical Society, 2000. Cerca con Google

M. Cao, A. Morse, and B. Anderson. Reaching a consensus in a dynamically changing environment a graphical approach. submitted to SIAM Journal on Control and Optimization. [Online] Available at http://www.eng.yale.edu/controls/pending/flockp1.pdf. Vai! Cerca con Google

M. Cao, D. A. Spielman, and E. M. Yeh. Accelerated gossip algorithms for distributed computation. In 44th Annual Allerton Conference on Communication, Control, and Computation., 2006. Cerca con Google

R. Carli, F. Fagnani, A. Speranzon, and S. Zampieri. Communication constraints in the average consensus problem. Automatica, to appear. Cerca con Google

G. Chen, G. Chen, and S. Hsu. Linear Stochastic Control Systems. CRC Press, 1995. Cerca con Google

L. G. D. Bauso and R. Pesenti. Distributed consensus in networks of dynamic agents. In Proceedings of IEEE Conference on Decision and Control (CDC’05), pages 7054—7059, 2005. Cerca con Google

P. J. Davis. Circulant matrices. A Wiley-Interscience Publication, Pure and Applied Mathematics. John Wiley & Sons, New York-Chichester Brisbane, 1979. Cerca con Google

J. L. Doob. Stochastic Processes. John Wiley & Sons, Inc., New York, 1953. Cerca con Google

F. R. Gantmacher. The theory of matrices. New York : Chelsea publ., 1959. Cerca con Google

J. Gubner. Distributed estimation and quantization. IEEE Transactions on Information Theory, 39(4):1456—1459, July 1993. May 17, 2007 DRAFT 35 Cerca con Google

Y. Hatano and M. Mesbahi. Agreement over random networks. IEEE Transactions on Automatic Control, 50(11):1867—1872, Nov. 2005. Cerca con Google

A. Jadbabaie, J. Lin, and A. S. Morse. Coordination of groups of mobile autonomous agents using nearest neighbor rules. IEEE Transactions on Automatic Control, 48(6):988—1001, June 2003. Cerca con Google

J..Xiao, A. Ribeiro, Z. Luo, and G. Giannakis. Distributed compression-estimation using wireless sensor networks. IEEE Signal Processing Magazine, pages 27—46, July 2006. Cerca con Google

J. Lin, A. Morse, and B. Anderson. The multi-agent rendezvous problem. In Proceedings of the 42nd IEEE Conference on Decision and Control (CDC’03), volume 2, pages 1508— 1513, December 2003. Cerca con Google

D. Looze, P. Houpt, N. S. Jr., and M. Athans. On decentralized estimation and control with application to freeway ram metering. IEEE Trans. on Aut. Contr., 23(2):268—275, 1978. Cerca con Google

Z. Luo and J. Tsitsiklis. Data fusion with minimal communication. IEEE Trans. on Information Theory, 40(5):1551—1563, Sept. 1994. Cerca con Google

L. Moreau. Stability of multiagent systems with time-dependent communication links. IEEE Transactions on Automatic Control, 50(2):169— 182, Feb. 2005. Cerca con Google

R. Murray, J. Fax, R. O. Saber, and D. Spanos. Consensus and cooperation in multi-agent networked systems. to appear in Proceedings of IEEE, February 2007. Cerca con Google

S. Muthukrihnan, B. Ghosh, and S. M. H. First and second order diffusive methods for rapid, coarse, distributed load balancing. Theory of Computing Systems, 31:331—354, 1998. Cerca con Google

R. Olfati-Saber. Distributed Kalman filter with embedded consensus filters. In Proceedings of the 44th IEEE Conference on Decision and Control, and European Control Conference, December 2005. Cerca con Google

R. Olfati-Saber. Ultrafast consensus in small-world networks. In Proceedings of the 2005 American Control Conference (ACC’05), volume 4, pages 2371— 2378, 2005. Cerca con Google

R. Olfati-Saber and R. M. Murray. Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans. Automat. Control, 49(9):1520—1533, 2004. Cerca con Google

R. Olfati-Saber and J. Shamma. Consensus filters for sensor networks and distributed sensor fusion. In Proceedings of the 44th IEEE Conference on Decision and Control, and European Control Conference, December 2005. Cerca con Google

A. Olshevsky and J. Tsitsiklis. Comvergence rates in distributed consensus and averaging. In Proc. of IEEE Conf. on Dec. and Control, pages 3387—3392, San Diego, CA, USA, December 2006. Cerca con Google

J. Predd, S. Kulkarni, and H. Poor. Regression in sensor networks: Traning distributively with alternating projections. Technical report, July 2005. Cerca con Google

W. Ren and R. Beard. Consensus seeking in multiagent systems under dynamically changing interaction topologies. IEEE Transactions on Automatic Control, 50(5):655— 661, May. 2005. Cerca con Google

A. Ribeiro and G. Giannakis. Bandwidth-constrained distributed estimation for wireless sensor networks - Part I: Gaussian case. IEEE Transactions on Signal Processing, 54(3):1131—1143, 2006. Cerca con Google

A. Ribeiro and G. Giannakis. Bandwidth-constrained distributed estimation for wireless sensor networks - Part II: Unknown probabilistic density function. IEEE Transactions on Signal Processing, 54(7):2784—2796, 2006. Cerca con Google

A. Ribeiro, G. Giannakis, and S. Roumeliotis. SOI-KF: Distributed Kalman filtering with low-cost communications using the sign of innovations. IEEE Transactions on Signal Processing, 54(12):4782—4795, 2006. Cerca con Google

I. Schizas, A. Ribeiro, and G. Giannakis. Consensus in ad hoc wsns with noisy links - Part I: Distributed estimation of deterministic signals. to appear in IEEE Transactions on Signal Processing, 2007. May 17, 2007 DRAFT 36 Cerca con Google

D. P. Spanos and R. M. Murray. Distributed sensor fusion using dynamic consensus. In Proccedings of the 16th IFAC World Congress, July 2005. Cerca con Google

D. P. Spanos, R. Olfati-Saber, and R. M. Murray. Distributed Kalman filtering in sensor networks with quantifiable performance. In Proccedings of the Information Processing for Sensor Networks (IPSN’05), 2005. Cerca con Google

A. Speranzon, C. Fischione, and K. Johansson. Distributed and collaborative estimation over wireless sensor networks. In Proceedings of the IEEE Conference on Decision and Control (CDC’06), pages 1025—1030, December 2006. Cerca con Google

J. N. Tsitsiklis, D. P. Bertsekas, and M. Athans. Distributed asynchronous deterministic and stochastic gradient optimization algorithms. IEEE Transactions on Automatic Control, 31(9):803—812, Sep. 1986. Cerca con Google

I. Vajda. On convergence of information contained in quantized observations. IEEE Trans. on Information Theory, 48(8):2163—2172, 2002. Cerca con Google

P. Venkitasubramaniam, G. Mergen, L. Tong, and A. Swami. Quantization for distributed estimation in large scale sensor networks. In Proc. of ICISIP, pages 121— 127, 2005. Cerca con Google

R. Viswanathan. A note on distributed estimation and sufficiency. IEEE Trans. on Information Theory, 39(5):1765—1767, 1993. Cerca con Google

L. Xiao and S. Boyd. Fast linear iterations for distributed averaging. Systems and Control Letters, 53(1):65—78, September 2004. Cerca con Google

L. Xiao, S. Boyd, and S.-J. Kim. Distributed average consensus with least-mean-square deviation. Journal of Parallel and Distributed Computing, 67(1):33—46, September 2007. Cerca con Google

L. Xiao, S. Boyd, and S. Lall. A scheme for robust distributed sensor fusion based on average consensus. In Proceedings of the Information Processing for Sensor Networks (IPSN’05), 2005. May 17, 2007 DRAFT Cerca con Google

Download statistics

Solo per lo Staff dell Archivio: Modifica questo record