Multi-agent systems (MASs) in open networks face dual security threats: Byzantine attacks that steer malicious consensus and eavesdroppers that steal private information. Existing resilient consensus protocol isolates Byzantine attacks by relying on (2f+1)-robust networks, which imposes stringent topological constraints and fails to provide privacy preservation simultaneously. To address this issue, an improved resilient consensus protocol withf(IRCP-f) is proposed, via absolute values of relative states, to defend againstf-local Byzantine attacks. This protocol only requires that an undirected and connected graph is (f+ 1)-robust instead of (2f+ 1)-robust. The properties of the dynamic network processed by the IRCP-fare analyzed, and the graph conditions for achieving average consensus are consequently satisfied. A fully distributed differentially private event-triggered average consensus (DPETAC) control scheme is then developed. With the DPETAC control scheme, convergence analysis, Zeno behavior analysis, accuracy analysis and privacy analysis are presented for the MAS. Finally, a numerical simulation illustrates the feasibility and effectiveness of the proposed privacy-preserving average consensus control scheme.

For a class of uncertain nonlinear stochastic multiagent systems, a consensus control strategy is proposed with an adjustable-time-varying-gain-based event-triggered extended state observer (ATVG-ETESO) via dual-terminal event-triggered mechanism (DTETM). The ATVG-ETESO estimates internal uncertainties and external stochastic disturbances. Its adjustable time-varying gain avoids peaking phenomenon at the initial stage and accelerates estimation error convergence. A DTETM with an adaptive threshold reduce communication burdens on both the input and output channels of the ATVG-ETESO. Theoretically, both the ATVG-ETESO estimation errors and the state consensus errors are bounded. Finally, two illustrative simulation examples are given to illustrate the effectiveness of the control strategy.