Adaptive Output Consensus Control for Unknown Discrete-Time Multiagent Systems With Sensor Uncertainties Under Stochastic Communication Protocol

This article focuses on the leader-follower output consensus (LFOC) control problem for unknown discrete-time multiagent systems (DTMASs) with sensor uncertainties under a stochastic communication protocol (SCP). An adaptive compensator is designed to eliminate the effects of sensor uncertainties, generating an adaptive estimation of the model output, which is then integrated into the feedback control law. Second, the exchange of information among agents in the multiagent system (MAS) is organized using an SCP governed by a Markov chain. At each communication instant, this protocol randomly selects a single state component of each agent for transmission. A unified Markov chain is constructed through the merging approach to represent the consensus error dynamics of the MAS. For dynamic systems with unknown parameters, a novel distributed adaptive output feedback controller is proposed to track the generated virtual reference signal and achieve LFOC under specific matching conditions. It is evident from the simulation results that the proposed controller guarantees output consensus control of the leader-follower closed-loop signals.