Abstract
The aim of this chapter is to design a distributed average tracking algorithm via nonsmooth feedback that could work for generic reference signals with bounded derivatives (The results in this chapter are based mainly on [5]. We have rewritten some parts in [5] and added several examples. See full copyright acknowledgement for non-original material at the end of the chapter). The challenge of distributed average tracking algorithm design lies in the presence of multiple reference signals which are time varying and do not converge. For this reason, consensus algorithms cannot be used directly for distributed average tracking, and a redesign is needed to take into account the changing trend of the reference signals. Although the reference signals are time varying, their derivatives are usually bounded. Thus, it is of interest to study the distributed average tracking problem for reference signals with bounded derivatives.
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- 2.
A special choice is \(z_i(0)=0\) for all \(i=1,\dots ,n\).
- 3.
Here, we use the term average tracking rather than dynamic consensus to emphasize the tracking nature of the problem.
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Acknowledgements
©2012 IEEE. Reprinted, with permission, from Fei Chen, Yongcan Cao, and Wei Ren. “Distributed average tracking of multiple time-varying reference signals with bounded derivatives.” IEEE Transactions on Automatic Control, vol. 57, no. 12, pp. 3169–3174, 2012.
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Chen, F., Ren, W. (2020). Distributed Average Tracking via Nonsmooth Feedback. In: Distributed Average Tracking in Multi-agent Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-39536-0_3
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DOI: https://doi.org/10.1007/978-3-030-39536-0_3
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