Sampled-data-based fault-tolerant consensus control for multi-agent systems: A data privacy preserving scheme

Abstract

This paper is concerned with the fault-tolerant consensus control problem for a general class of linear continuous-time multi-agent systems (MASs) with the data privacy preserving (DPP) constraints. Rather than employing the traditional cryptographic mechanism, we develop a novel dynamic-quantization-based DPP scheme from a control-theoretic perspective. Under our developed DPP scheme, the sampled, quantized, released, received and recovered data is used to design a fault-tolerant controller. With the adopted controller structure, the consensus of the MASs is guaranteed where the size of the data transmitted among agents can be made finite. A series of numerical examples are given and the comparative analysis is carried out to illustrate the effectiveness of the developed consensus control scheme.