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Distributed average tracking with input saturation
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DOI：10.1007/s11071-017-3844-z.png)
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Abstract
En 中文
In this paper, the distributed average tracking (DAT) problem of a multi-agent system with input saturation is considered, whose objective is to make each agent track the average of a group of time-varying reference signals by local saturated inputs. This paper proposes two algorithms based on the techniques of low-gain feedback and nonsmooth feedback. The first algorithm considers reference signals without external inputs under the low-gain feedback scheme. We show that if the system matrix of the references is negative semi-definite, then the DAT error will be ultimately upper bounded. The other algorithm considers reference signals with bounded inputs, where the idea of nonsmooth feedback is employed. Finally, two simulation examples are presented to validate the theoretical results.
Keywords:
Consensus
Input saturation
Low-gain feedback
Nonsmooth feedback
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