Abstract
Control and estimation of second-order distributed parameter systems are of importance in mechanical systems. In particular, flexible structures can be modeled as second-order distributed parameter systems. This paper investigates adaptive consensus filtering for a class of second-order distributed parameter systems under an abstract framework. We propose an adaptive consensus mechanism to minimize the disagreement among all local filters consisting of different sensor nodes and written in the natural setting of a second-order formulation with an additional coupling. A parameter-dependent Lyapunov function is presented to analyze the stability of the collective dynamics, that is, all filters agree with each other and converge to the true state of the second-order system. The performance is demonstrated on a numerical example of a second-order partial differential equation with point measurements.
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Acknowledgments
The authors gratefully thank the Editor-in-Chief, Prof. M. N. S. Swamy, as well as the associate editor and anonymous reviewers for their constructive suggestions and comments. We would like also to acknowledge our great debt to Ricardo G. Sanfelice and Sean Phillips for carefully reading through the paper. This work is partially supported by National Natural Science Foundation of China (61473136, 61174021), the Fundamental Research Funds for the Central Universities (JUSRP51322B), the 111 Project (B12018) and China Scholarship Council (201406795004).
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Lou, X., Cui, B. Adaptive Consensus Filters for Second-Order Distributed Parameter Systems Using Sensor Networks. Circuits Syst Signal Process 34, 2801–2818 (2015). https://doi.org/10.1007/s00034-015-9976-9
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DOI: https://doi.org/10.1007/s00034-015-9976-9