By Keyou You, Nan Xiao, Lihua Xie
This monograph makes a speciality of characterizing the soundness and function effects of placing limited-capacity conversation networks inside of a keep watch over loop. The textual content indicates how integration of the guidelines of regulate and estimation with these of communique and knowledge conception can be utilized to supply very important insights touching on numerous basic difficulties such as:
· minimal facts cost 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 printed among the topological entropy of linear dynamical platforms and the capacities of conversation channels. The layout of a logarithmic quantizer for the stabilization of linear platforms lower than numerous community environments can be widely mentioned and suggestions to many difficulties of Kalman filtering with intermittent observations are demonstrated.
Analysis and layout of Networked regulate Systems will curiosity keep an eye on 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 an eye on who're learning such systems.
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Additional info for Analysis and Design of Networked Control Systems
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. K. You, L. Xie, Minimum data rate for mean square stabilization of discrete LTI systems over lossy channels. IEEE Trans. Autom. Control 55(10), 2373–2378 (2010) 58. A. Matveev, A. Savkin, Comments on control over noisy channels and relevant negative results. IEEE Trans. Autom. Control 50(12), 2105–2110 (2005) 59. A. Matveev, A. Savkin, An analogue of Shannon information theory for detection and stabilization via noisy discrete communication channels.
2 Proof of Sufficiency Similarly, there is no loss of generality to assume that all the eigenvalues of A are unstable. The unknown quantity of the system to the controller is originated from the initial state x0 , whose uncertainty growth rate due to the system dynamics is given by |λi |≥1 |λi |. To achieve the asymptotic stability, it requires the controller to estimate x0 with the estimation error decaying at a rate faster than |λi |≥1 |λi |. 5), the controller can thus achieve this goal by appropriately designing a causal coder.
The main results are presented in Sect. 2, where we start at the investigation of the minimum data rate for single input systems followed by multiple input systems in Sect. 3. Concluding remarks are made in Sect. 4. 1 Problem Formulation Consider a discrete LTI system xk+1 = Axk + Bu k , © Springer-Verlag London 2015 K. 1) 39 40 4 Data Rate Theorem for Stabilization Over Erasure Channels Fig. 1 Network configuration Decoder Channel sk uk γk−1 Encoder System xk fk Controller where xk ∈ Rn is the measurable state for feedback and u k ∈ Rm is the control input.
Analysis and Design of Networked Control Systems by Keyou You, Nan Xiao, Lihua Xie
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