Abstract
Various control strategies achieve results in different aspects of both research and practice on Network Control Systems (NCSs). Aiming at NCSs with short delay which is less than one sampling period, from the system state identification point of view, the concept of network delay noises (NDNs) is presented, Kalman filter based on NCSs is deduced, the major factors impacting on the error variance of Kalman filter based on NCSs are explained, convergence formula of error variance of a priori estimate and convergence value of error variance of a posteriori estimate are given. At last, the simulation proves that the Kalman filter based on NCSs is feasible.
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References
Mo-Yuan, C., Yodyium, T.: Network-Based Control Systems: A Tutorial, IECON’01. In: The 27th Annual Conference of the IEEE Industrial Electronics Society (2001)
Li, H.B., Sun, Z.Q., Sun, F.C.: Networked control systems: an overview of state-of-the-art and the prospect in future research. Control Theory & Applications 27, 238–243 (2010)
Liu, B., Tang, W.S.: Modern control Theory. China machine press, Beijing (2006)
Dan, S.: Optimal State Estimation. A John Wiley & Sons, Inc., Publication, Chichester (2006)
Greg W., Gary B.: An Introduction to the Kalman Filter, TR 95–041, Department of Computer Science University of North Carolina at Chapel Hill, NC 27599-3175 (2006)
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yu, Xm., jiang, Jp. (2010). A State Identification Method of Networked Control Systems. In: Li, K., Fei, M., Jia, L., Irwin, G.W. (eds) Life System Modeling and Intelligent Computing. ICSEE LSMS 2010 2010. Lecture Notes in Computer Science, vol 6328. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15621-2_10
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DOI: https://doi.org/10.1007/978-3-642-15621-2_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15620-5
Online ISBN: 978-3-642-15621-2
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