By Keyou You, Nan Xiao, Lihua Xie
This monograph specializes in characterizing the soundness and function outcomes of placing limited-capacity verbal exchange networks inside of a regulate loop. The textual content indicates how integration of the guidelines of keep watch over and estimation with these of conversation and knowledge concept can be utilized to supply very important insights relating a number of primary difficulties such as:
· minimal information price 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 basic hyperlink is published among the topological entropy of linear dynamical platforms and the capacities of verbal exchange channels. The layout of a logarithmic quantizer for the stabilization of linear structures lower than a variety of community environments can also be greatly 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 regulate theorists and engineers operating with networked platforms and should even be used as a source for graduate scholars with backgrounds in utilized arithmetic, communications or keep watch over who're learning such systems.
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Additional resources for Analysis and Design of Networked Control Systems
1). We have the following main result. 1 and the network configuration in Fig. d. packet loss model with packet loss rate p ∈ (0, 1). 2) where M(A) is the Mahler measure of the LTI system. 3) where HT (A) is the topological entropy of the LTI system. 2 Due to the existence of packet loss, additional bits are required to counter the packet loss effect on the stabilizability of the system. 3) which is a function of the packet loss rate and the intrinsic entropy of the system. One can easily verify that this term is a monotonically increasing function of packet loss rate p satisfying that 0 < p < M(A)−2 .
In , this problem was studied by using an information-theoretic approach. It is fair to say that the data rate problem over a noiseless digital channel is relatively mature. References 1. A. Gersho, R. Gray, Vector Quantization and Signal Compression (Kluwer Academic Publishers, Norwell, 1991) 2. T. Cover, J. Thomas, Elements of Information Theory (Wiley-Interscience, New York, 2006) 3. R. Horn, C. Johnson, Matrix Analysis (Cambridge University Press, Cambridge, 1985) References 37 4. G. Nair, R.
J. Robust Nonlinear Control 19(18), 1993–2015 (2009) 54. S. Dey, A. Leong, J. Evans, Kalman filtering with faded measurements. Automatica 45(10), 2223–2233 (2009) 55. N. Martins, M. Dahleh, N. Elia, Feedback stabilization of uncertain systems in the presence of a direct link. IEEE Trans. Autom. Control 51(3), 438–447 (2006) 56. P. Minero, M. Franceschetti, S. Dey, G. Nair, Data rate theorem for stabilization over timevarying feedback channels. IEEE Trans. Autom. Control 54(2), 243–255 (2009) 57.
Analysis and Design of Networked Control Systems by Keyou You, Nan Xiao, Lihua Xie