By Keyou You, Nan Xiao, Lihua Xie
This monograph specializes in characterizing the steadiness and function results of putting limited-capacity verbal exchange networks inside of a regulate loop. The textual content indicates how integration of the tips of keep an eye on and estimation with these of verbal exchange and data thought can be utilized to supply very important insights touching on a number of primary difficulties such as:
· minimal information fee for stabilization of linear structures over noisy channels;
· minimal community requirement for stabilization of linear platforms over fading channels; and
· balance of Kalman filtering with intermittent observations.
A primary hyperlink is published among the topological entropy of linear dynamical structures and the capacities of communique channels. The layout of a logarithmic quantizer for the stabilization of linear platforms less than numerous community environments is usually broadly mentioned and options to many difficulties of Kalman filtering with intermittent observations are demonstrated.
Analysis and layout of Networked keep watch over Systems will curiosity keep an eye on theorists and engineers operating with networked platforms and will even be used as a source for graduate scholars with backgrounds in utilized arithmetic, communications or regulate who're learning such systems.
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Additional info for Analysis and Design of Networked Control Systems
Automatica 49(2), 360–369 (2013) 68. A. Ribeiro, G. Giannakis, S. Roumeliotis, SOI-KF: distributed Kalman filtering with low-cost communications using the sign of innovations. IEEE Trans. Signal Process. 54(12), 4782– 4795 (2006) 69. K. You, L. Xie, S. Sun, W. Xiao, Multiple-level quantized innovation Kalman filter, in Proceedings of 17th IFAC World Congress, pp. 1420–1425 (2008) 70. V. Borkar, S. Mitter, S. Tatikonda, Optimal sequential vector quantization of Markov sources. SIAM J. Control Optim.
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61(14), 3521–3531 (2013) 84. J. Wu, Q. Jia, K. Johansson, L. Shi, Event-based sensor data scheduling: trade-off between sensor communication rate and estimation quality. Preprint (2011) 85. G. Battistelli, A. Benavoli, L. Chisci, Data-driven communication for state estimation with sensor networks. Automatica 48(5), 926–935 (2012) 86. C. Wikle, N. Cressie, A dimension-reduced approach to space-time Kalman filtering. Biometrika 86(4), 815–829 (1999) 87. I. Schizas, G. Giannakis, Z. Luo, Distributed estimation using reduced-dimensionality sensor observations.