Bipartite Consensus Control for Nonlinear Multiagent Systems With Power Uncertainty under Deception Attacks

This article investigates a class of bipartite consensus control problem with actuators under deception attacks. Conventional multi-agent systems require input power to be a known positive integer. We have considered a more general system model for this, which is a multi-agent system with uncertain power, where the output power of each agent is unknown. Considering the problem of unknown direction caused by deception attacks on the system, a special class of Nussbaum functions is introduced, and an adaptive neural control protocol is designed. This protocol not only implements bipartite consensus control, but also ensures that all signals in the system are bounded. The final simulation results verified the effectiveness of the algorithm.